Triple
T3705038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabrielino-Fernandeño |
E80870
|
entity |
| Predicate | hasPlaceNameLegacyIn |
P17611
|
FINISHED |
| Object | Los Angeles area toponyms |
—
|
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: Los Angeles area toponyms | Statement: [Gabrielino-Fernandeño, hasPlaceNameLegacyIn, Los Angeles area toponyms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlaceNameLegacyIn Context triple: [Gabrielino-Fernandeño, hasPlaceNameLegacyIn, Los Angeles area toponyms]
-
A.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
-
B.
locatedInFormerNamePlace
Indicates that an entity is located in a place that is referred to by its former or historical name rather than its current name.
-
C.
hasTraditionalName
chosen
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
-
D.
hasMetropolitanAreaName
Indicates that an entity is associated with a metropolitan area identified by a specific name.
-
E.
hasHeritageSiteNamedAfter
Indicates that one entity has a heritage site that is named after another entity.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc54bbfcc8190bec9c16e3749c3b1 |
completed | March 8, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.