Triple
T26839474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fernandomania |
E675737
|
entity |
| Predicate | cityMostAssociated |
P24465
|
FINISHED |
| Object | Los Angeles |
—
|
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: Los Angeles | Statement: [Fernandomania, cityMostAssociated, Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityMostAssociated Context triple: [Fernandomania, cityMostAssociated, Los Angeles]
-
A.
cityAssociatedWith
chosen
Indicates that there is a notable connection or relationship between a city and another entity, such as relevance, involvement, or contextual association.
-
B.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or entity.
-
C.
nearestLargeUrbanArea
Indicates that one entity is the closest major city or large urban center to the other entity.
-
D.
principalCityOf
Indicates that a city serves as the main or most important city (often administrative, economic, or cultural center) of a specified region or area.
-
E.
primaryCity
Indicates that one city serves as the main or most important city associated with a given region, entity, or context.
- 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_69eee9b8d5e88190a07d3455c0fbb21f |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61b4573188190ab57fe26f5b745fb |
completed | May 2, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:07 a.m.