Triple
T7544529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montpellier |
E178364
|
entity |
| Predicate | distanceToMediterraneanCoast |
P16475
|
FINISHED |
| Object | about 10 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 10 km | Statement: [Montpellier, distanceToMediterraneanCoast, about 10 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMediterraneanCoast Context triple: [Montpellier, distanceToMediterraneanCoast, about 10 km]
-
A.
distanceFromMediterranean
chosen
Indicates the measured spatial distance between a given location and the Mediterranean Sea.
-
B.
distanceFromCoast
Indicates the measured spatial separation between a location and the nearest point on a coastline.
-
C.
distanceToBlackSea
Indicates the measured spatial distance between a given entity and the Black Sea.
-
D.
dateToReachMediterranean
Indicates the date on which an entity is expected or scheduled to arrive at, or first reach, the Mediterranean.
-
E.
distanceFromTelAviv_km
Indicates the physical distance, measured in kilometers, between a given place and Tel Aviv.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f898069881909fa8f9c885c4565b |
completed | March 27, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69c6f4daad6c8190af2b8ae88d2c8cb7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.