Triple
T32488457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rancho Niguel |
E830311
|
entity |
| Predicate | toponymicRelation |
P122228
|
FINISHED |
| Object | shares root name with Laguna Niguel |
—
|
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: shares root name with Laguna Niguel | Statement: [Rancho Niguel, toponymicRelation, shares root name with Laguna Niguel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toponymicRelation Context triple: [Rancho Niguel, toponymicRelation, shares root name with Laguna Niguel]
-
A.
hasToponymicAssociation
chosen
Indicates a relationship where one entity is associated with, derived from, or named after a particular place or geographic name (toponym).
-
B.
isToponymOf
Indicates that one entity is a place name (toponym) that refers to the location represented by the other entity.
-
C.
hasToponymicDerivatives
Indicates that a name or term serves as the source from which related place-based or toponymic names are derived.
-
D.
toponymicFunction
Indicates that one entity functions as a place-related name or designation for another entity, typically identifying or characterizing it by a geographic location.
-
E.
toponymRefersTo
Indicates that a place name (toponym) designates or refers to a specific geographic entity or location.
- 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c3f9e5448190b47486b32738e7b0 |
completed | May 3, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:58 a.m.