Triple
T6397361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foreign Affairs Committee (Spain) |
E143972
|
entity |
| Predicate | hasOfficers |
P4012
|
FINISHED |
| Object | chair |
—
|
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: chair | Statement: [Foreign Affairs Committee (Spain), hasOfficers, chair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficers Context triple: [Foreign Affairs Committee (Spain), hasOfficers, chair]
-
A.
officersAre
Indicates that certain individuals hold the role or position of officers within a specified group, organization, or context.
-
B.
isOfficerOf
chosen
Indicates that one entity holds an official position, role, or office within another entity (such as an organization, group, or institution).
-
C.
hasListOfOfficeHolders
Indicates that an entity is associated with a collection or record enumerating the individuals who have held a particular office or position.
-
D.
memberHoldsOffice
Indicates that a member occupies or serves in a specific official position or office within an organization or governing body.
-
E.
hasJudicialOfficer
Indicates that an entity is associated with or served by a specific judicial officer (such as a judge or magistrate) responsible for legal or court-related functions.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06896d180819091548a728e903184 |
completed | March 22, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69c060f25c088190b433f78553ff1d84 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:35 p.m.