Triple
T34717990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robles Department |
E1000830
|
entity |
| Predicate | hasHeadTown |
P193369
|
FINISHED |
| Object | Fernández |
—
|
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: Fernández | Statement: [Robles Department, hasHeadTown, Fernández]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHeadTown Context triple: [Robles Department, hasHeadTown, Fernández]
-
A.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
B.
hasVillageAtHead
Indicates that a village is located at the head (source or upper end) of a geographic feature such as a valley, river, or bay.
-
C.
hasTownshipSeat
Indicates that a particular location serves as the administrative or governing center (seat) of a specified township.
-
D.
hasTownship
Indicates that one administrative area or jurisdiction includes or is associated with a specific township.
-
E.
administrativeHeadquarterTown
chosen
Indicates the town that serves as the administrative headquarters for a given entity, such as an organization or territorial unit.
- 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_69f76dad3f108190a280fd0a2f4ee89a |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
Created at: May 3, 2026, 3:59 p.m.