Triple
T179067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The West Wing |
E3643
|
entity |
| Predicate | portraysOffice |
P7009
|
FINISHED |
| Object | President of the United States |
—
|
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: President of the United States | Statement: [The West Wing, portraysOffice, President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysOffice Context triple: [The West Wing, portraysOffice, President of the United States]
-
A.
hasOffice
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
B.
electedOffice
Indicates that an entity holds or has held a particular office or position as a result of an election.
-
C.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
D.
oneOfTheGreatOfficesOfState
Indicates that the entity holds or pertains to one of the highest-ranking senior government positions traditionally recognized as the Great Offices of State.
-
E.
leftOffice
Indicates that an entity ceased holding or performing the duties of a particular office or position.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25900709c8190a65e778936be5dd5 |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2566b53d481909c0ed40dd3719e8c |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2582b7f648190b0ef676b8bdc1c65 |
completed | Feb. 28, 2026, 2:51 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.