Triple
T35010519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. House |
E1009928
|
entity |
| Predicate | offersToPlayer |
P63281
|
FINISHED |
| Object | alliance to secure New Vegas |
—
|
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: alliance to secure New Vegas | Statement: [Mr. House, offersToPlayer, alliance to secure New Vegas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersToPlayer Context triple: [Mr. House, offersToPlayer, alliance to secure New Vegas]
-
A.
offersGame
Indicates that one entity provides or makes a game available to another entity.
-
B.
offersObject
chosen
Indicates that a subject provides or makes available a specific object to another party as an offer.
-
C.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
D.
offersAward
Indicates that one entity grants or makes available an award or prize to another entity.
-
E.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
- F. None of above.
Provenance (3 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe30bc64308190b603ff1b30c2aeee |
completed | May 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fe2f7175b081908dd61e1513620bbe |
completed | May 8, 2026, 6:46 p.m. |
Created at: May 3, 2026, 4:01 p.m.