Triple
T5937405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coachella |
E132076
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | La Quinta |
E132078
|
NE 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: La Quinta | Statement: [Coachella, locatedNear, La Quinta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Quinta Context triple: [Coachella, locatedNear, La Quinta]
-
A.
La Quinta
chosen
La Quinta is a resort city in Southern California known for its golf courses, luxury hotels, and desert scenery.
-
B.
Los Pinos
Los Pinos is the former official residence and offices of the President of Mexico, located in Mexico City’s Bosque de Chapultepec.
-
C.
Hacienda
Hacienda is the commonly used Spanish name for Puerto Rico’s Department of Treasury, the government agency responsible for tax collection and fiscal management on the island.
-
D.
Buena Vista
Buena Vista is a brand name historically used by The Walt Disney Company for its international film distribution and related entertainment operations.
-
E.
Buena Vista
Buena Vista is a small mountain town in central Colorado known for its outdoor recreation, especially whitewater rafting on the Arkansas River and access to the Collegiate Peaks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c038eca9688190adeed21df058daf1 |
completed | March 22, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c06f979881908d7e98ee674f1ff2 |
completed | March 23, 2026, 4:24 a.m. |
Created at: March 22, 2026, 4:01 p.m.