Triple
T18082463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Caddo Company |
E432728
|
entity |
| Predicate | roleInScarface1932 |
P129728
|
FINISHED |
| Object | backer |
—
|
LITERAL FINISHED |
How this triple was built (2 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: backer | Statement: [The Caddo Company, roleInScarface1932, backer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInScarface1932 Context triple: [The Caddo Company, roleInScarface1932, backer]
-
A.
roleInDa5Bloods
Indicates that an entity had an acting role in the film "Da 5 Bloods."
-
B.
roleInManOnFire
Indicates that an entity has a role or participation in the work titled "Man on Fire."
-
C.
roleInCareerOfAlCapone
Indicates the specific role or involvement an entity had in the professional or criminal career of Al Capone.
-
D.
roleInFamousPlay
Indicates that an entity portrays or has portrayed a specific character in a well-known theatrical play.
-
E.
roleInSyriana
Indicates that one entity has a specific role or involvement in the context of "Syriana," such as participation, function, or contribution related to it.
- F. None of above. chosen
Provenance (4 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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9fb42888190919fe711a281bd7c |
completed | April 19, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69e3f90d42ec8190b7afa70b005f287e |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:27 a.m.