Triple
T26100427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barra de Navidad |
E658383
|
entity |
| Predicate | distanceToManzanillo_km |
P194549
|
FINISHED |
| Object | about 60 |
—
|
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: about 60 | Statement: [Barra de Navidad, distanceToManzanillo_km, about 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToManzanillo_km Context triple: [Barra de Navidad, distanceToManzanillo_km, about 60]
-
A.
distanceToMérida
Indicates the spatial distance between a given entity and the location Mérida.
-
B.
distanceToCancun
Indicates the measured or calculated spatial distance between a given entity and the location of Cancun.
-
C.
distanceFromSantoDomingo
Indicates the spatial distance between a given entity and the location of Santo Domingo.
-
D.
distanceToGuadalajara_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Guadalajara.
-
E.
distanceToHolguin
Indicates the measured spatial distance between a given entity and the location of Holguin.
- F. None of above. chosen
Provenance (4 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_69ee5bc09c288190bc42a11972841383 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69fd7b042a548190b3abe31bc3258278 |
completed | May 8, 2026, 5:56 a.m. |
Created at: April 26, 2026, 7:54 p.m.