Triple
T28445552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anillaco, La Rioja, Argentina |
E715829
|
entity |
| Predicate | distanceToChilecito |
P201586
|
FINISHED |
| Object | about 50 km |
—
|
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 50 km | Statement: [Anillaco, La Rioja, Argentina, distanceToChilecito, about 50 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToChilecito Context triple: [Anillaco, La Rioja, Argentina, distanceToChilecito, about 50 km]
-
A.
distanceToNeuquénCity_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Neuquén.
-
B.
distanceFromSaltaByRoad_km
Indicates the distance in kilometers between an entity and Salta when traveling by road.
-
C.
distanceToSantiago_km
Indicates the physical distance, measured in kilometers, between a given location and Santiago.
-
D.
distanceToSanMiguelDeTucumán
Indicates the spatial distance between a given entity and the location of San Miguel de Tucumán.
-
E.
distanceToSanSebastián
Indicates the spatial distance between a given entity and the location of San Sebastián.
- 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_69efd6b44550819094ae991b553d9fc3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a000a1d8fa88190a1d82ac746565c48 |
completed | May 10, 2026, 4:31 a.m. |
| PD | Predicate disambiguation | batch_6a0008b26eb88190ae03b2309a614774 |
completed | May 10, 2026, 4:25 a.m. |
| PDg | Predicate description generation | batch_6a000a1c8f8881908293ab4f7207d25f |
completed | May 10, 2026, 4:31 a.m. |
Created at: April 28, 2026, 1:48 a.m.