Triple
T11251926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billie Lurk |
E266338
|
entity |
| Predicate | roleInDishonored2 |
P98718
|
FINISHED |
| Object | boat captain for the Dreadful Wale |
—
|
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: boat captain for the Dreadful Wale | Statement: [Billie Lurk, roleInDishonored2, boat captain for the Dreadful Wale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInDishonored2 Context triple: [Billie Lurk, roleInDishonored2, boat captain for the Dreadful Wale]
-
A.
roleInBladeII
Indicates that an entity has a specific role or participation in the movie "Blade II."
-
B.
roleInCitadel
Indicates the specific function, position, or responsibility an entity holds within a citadel or fortified complex.
-
C.
roleInWatchmen
Indicates that one entity has a specific role or function within the context of the work "Watchmen" in relation to the other entity.
-
D.
deFactoRole
Indicates that an entity effectively functions in a role or capacity in practice, even if that role is not formally or officially assigned.
-
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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e933648481909873094bc89ed041 |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d78793c00481908a3f764b610b77a4 |
completed | April 9, 2026, 11:03 a.m. |
| PDg | Predicate description generation | batch_69d796cf74308190a5b29d0dd82954a2 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:31 p.m.