Triple
T35434680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ana María Hidalgo Aleu |
E1024168
|
entity |
| Predicate | wasDeputyMayorOf |
P182974
|
FINISHED |
| Object | Paris |
—
|
NE NERFINISHED |
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: Paris | Statement: [Ana María Hidalgo Aleu, wasDeputyMayorOf, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasDeputyMayorOf Context triple: [Ana María Hidalgo Aleu, wasDeputyMayorOf, Paris]
-
A.
wasDeputyIn
Indicates that an entity served in the role of deputy within a specified organization, office, or jurisdiction during a particular period.
-
B.
wasCityCommissionerOf
Indicates that a person previously held the official position of city commissioner for a particular city or municipal jurisdiction.
-
C.
deputyOf
Indicates that one entity serves as the subordinate or second-in-command to another, acting with delegated authority on their behalf.
-
D.
formerMayor
Indicates that the subject once held the position of mayor of the object entity but no longer does.
-
E.
hasViceMayor
Indicates that an entity holds the position of vice mayor for a given administrative or governmental body.
- 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_69f76df743c48190aecb6dd79efb0d95 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f795babc948190b17d885f6ce1f653 |
completed | May 3, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 3, 2026, 4:04 p.m.