Triple
T34610972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vendôme |
E888734
|
entity |
| Predicate | distanceToParis_km |
P10703
|
FINISHED |
| Object | about 180 |
—
|
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 180 | Statement: [Vendôme, distanceToParis_km, about 180]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToParis_km Context triple: [Vendôme, distanceToParis_km, about 180]
-
A.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
-
B.
distanceFromParisCenter
chosen
Indicates the measured distance between a given location and the central point of Paris.
-
C.
distanceFromParisGareDeLyon
Indicates the distance between an entity and Paris Gare de Lyon railway station.
-
D.
distanceToMarseilleKilometers
Indicates the physical distance, measured in kilometers, between a given location or entity and the city of Marseille.
-
E.
distanceToPauKmApprox
Indicates an approximate distance, measured in kilometers, from an entity to the location Pau.
- 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_69f349d584e08190b40b9f6281ad50c4 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:03 a.m.