Triple
T20011459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamnet |
E494599
|
entity |
| Predicate | publisher |
P29
|
FINISHED |
| Object |
Tinder Press
Tinder Press is a literary imprint of Headline Publishing Group known for publishing high-quality, critically acclaimed fiction.
|
E1405124
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tinder Press | Statement: [Hamnet, publisher, Tinder Press]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tinder Press Context triple: [Hamnet, publisher, Tinder Press]
-
A.
Matchmakers
Matchmakers is a popular Ukrainian comedy television series produced by Kvartal 95 Studio that follows the humorous clashes and relationships between two very different families.
-
B.
Lovehunter
Lovehunter is a 1979 hard rock album by British band Whitesnake, noted for its bluesy sound and controversial cover art.
-
C.
The MatchMaker
The MatchMaker is a romantic comedy film best known for its lighthearted story about love and relationships, released in the late 1990s.
-
D.
Match.com
Match.com is one of the earliest and most prominent online dating services, connecting singles worldwide through its web and mobile platforms.
-
E.
Hinge
Hinge is a dating app designed to foster serious, long-term relationships by encouraging users to build detailed profiles and engage in more meaningful conversations.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tinder Press Triple: [Hamnet, publisher, Tinder Press]
Generated description
Tinder Press is a literary imprint of Headline Publishing Group known for publishing high-quality, critically acclaimed fiction.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tinder Press Target entity description: Tinder Press is a literary imprint of Headline Publishing Group known for publishing high-quality, critically acclaimed fiction.
-
A.
Matchmakers
Matchmakers is a popular Ukrainian comedy television series produced by Kvartal 95 Studio that follows the humorous clashes and relationships between two very different families.
-
B.
Lovehunter
Lovehunter is a 1979 hard rock album by British band Whitesnake, noted for its bluesy sound and controversial cover art.
-
C.
The MatchMaker
The MatchMaker is a romantic comedy film best known for its lighthearted story about love and relationships, released in the late 1990s.
-
D.
Match.com
Match.com is one of the earliest and most prominent online dating services, connecting singles worldwide through its web and mobile platforms.
-
E.
Hinge
Hinge is a dating app designed to foster serious, long-term relationships by encouraging users to build detailed profiles and engage in more meaningful conversations.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623773d88190826616a02d3c3e69 |
completed | April 20, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0805137f2081908f63e0ab7fe5d3d4 |
completed | May 16, 2026, 5:48 a.m. |
| NEDg | Description generation | batch_6a08056969748190aeddd8a11f6904cd |
completed | May 16, 2026, 5:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0805f206748190845ab7eb7042d679 |
completed | May 16, 2026, 5:51 a.m. |
Created at: April 11, 2026, 3:33 p.m.