Triple
T22689048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyson |
E560997
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object |
Tycen
Tycen is a masculine given name, typically considered a modern variant of the name Tyson.
|
E1548811
|
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: Tycen | Statement: [Tyson, hasVariantSpelling, Tycen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tycen Context triple: [Tyson, hasVariantSpelling, Tycen]
-
A.
Tillion
Tillion is the surname of Germaine Tillion, a renowned French ethnologist, Resistance member during World War II, and later a prominent public intellectual.
-
B.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
C.
Teran
Teran is a robust, dark-skinned red wine grape variety traditionally grown in the Istrian region, known for producing deeply colored, high-acidity wines.
-
D.
Tyrena
Tyrena is a notable city on the planet Corellia in the Star Wars universe, known for its urban sprawl and role as a regional hub.
-
E.
Yrica Quell
Yrica Quell is a former Imperial TIE fighter pilot who defects to the New Republic and leads the misfit pilots of Alphabet Squadron in the Star Wars canon novels.
- 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: Tycen Triple: [Tyson, hasVariantSpelling, Tycen]
Generated description
Tycen is a masculine given name, typically considered a modern variant of the name Tyson.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tycen Target entity description: Tycen is a masculine given name, typically considered a modern variant of the name Tyson.
-
A.
Tillion
Tillion is the surname of Germaine Tillion, a renowned French ethnologist, Resistance member during World War II, and later a prominent public intellectual.
-
B.
Tynaarlo
Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
-
C.
Teran
Teran is a robust, dark-skinned red wine grape variety traditionally grown in the Istrian region, known for producing deeply colored, high-acidity wines.
-
D.
Tyrena
Tyrena is a notable city on the planet Corellia in the Star Wars universe, known for its urban sprawl and role as a regional hub.
-
E.
Yrica Quell
Yrica Quell is a former Imperial TIE fighter pilot who defects to the New Republic and leads the misfit pilots of Alphabet Squadron in the Star Wars canon novels.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789931148190925ce9038c16413b |
completed | April 29, 2026, 3:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b73f90304819084b6c4c944cbf504 |
completed | May 18, 2026, 8:18 p.m. |
| NEDg | Description generation | batch_6a0b7505c99081908a9faac30451e6e8 |
completed | May 18, 2026, 8:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b761510b48190a09722be3fca7e93 |
completed | May 18, 2026, 8:27 p.m. |
Created at: April 17, 2026, 3:13 p.m.