Triple
T37368527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tovaangar |
E927774
|
entity |
| Predicate | hasModernCityWithin |
P58091
|
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: [Tovaangar, hasModernCityWithin, Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModernCityWithin Context triple: [Tovaangar, hasModernCityWithin, Los Angeles]
-
A.
containsModernCity
chosen
Indicates that one geographic or administrative region includes within its boundaries a currently existing modern city.
-
B.
hasModernNearbyCity
Indicates that an entity is located near or in proximity to a contemporary, currently existing city.
-
C.
hasModernRegionCapital
Indicates that a region is associated with the city that currently serves as its modern administrative or political capital.
-
D.
hasAncientCityState
Indicates that one entity possesses, contains, or is associated with an ancient city-state as part of its historical or geographical context.
-
E.
hasHistoricCity
Indicates that an entity possesses, contains, or is associated with a city recognized for its historical significance.
- 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff8cecbf048190860b9f72b8753f5c |
completed | May 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69ff8c4c39dc8190b5bf35adc1bae7c6 |
completed | May 9, 2026, 7:34 p.m. |
Created at: May 3, 2026, 4:16 p.m.