Triple
T36995929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Invisible Stripes |
E915226
|
entity |
| Predicate | hasHumphreyBogartRole |
P102768
|
FINISHED |
| Object |
Chuck Martin
Chuck Martin is a fictional criminal character portrayed by Humphrey Bogart in the 1939 crime drama film "Invisible Stripes."
|
E2209807
|
NE FINISHED |
How this triple was built (3 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: Chuck Martin | Statement: [Invisible Stripes, hasHumphreyBogartRole, Chuck Martin]
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: Chuck Martin Triple: [Invisible Stripes, hasHumphreyBogartRole, Chuck Martin]
Generated description
Chuck Martin is a fictional criminal character portrayed by Humphrey Bogart in the 1939 crime drama film "Invisible Stripes."
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumphreyBogartRole Context triple: [Invisible Stripes, hasHumphreyBogartRole, Chuck Martin]
-
A.
hasJoanFontaineRole
Indicates that an entity has a role played by Joan Fontaine in a film, television, or theatrical production.
-
B.
hasRitaHayworthRole
Indicates that an entity has a role or character associated with Rita Hayworth, such as portraying her or a role closely linked to her.
-
C.
hasGingerRogersRole
Indicates that an entity is assigned or associated with a role specifically identified as the "Ginger Rogers" role in a given context or production.
-
D.
humphreyBogartRole
chosen
Indicates that one entity is a role or character portrayed by Humphrey Bogart in a film, play, or other performance.
-
E.
hasGlennFordRole
Indicates that an entity has a role played by the actor Glenn Ford.
- F. None of above.
Provenance (6 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb34e5576881909394355c8ec6ddd2 |
completed | May 6, 2026, 12:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3e57629afc819098bc33f57d1d5369 |
completed | June 26, 2026, 10:41 a.m. |
| NEDg | Description generation | batch_6a3e590379ec81908abaeb5d94e0a87a |
completed | June 26, 2026, 10:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3e848175bc8190965c8c71a1889cb9 |
completed | June 26, 2026, 1:54 p.m. |
| PD | Predicate disambiguation | batch_69fb2f6171e88190bf1e0ee6a644b6a9 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:14 p.m.