Triple
T10085230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toulouse–Hendaye |
E215201
|
entity |
| Predicate | connectsInlandCityToCoast |
P91982
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Toulouse–Hendaye, connectsInlandCityToCoast, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsInlandCityToCoast Context triple: [Toulouse–Hendaye, connectsInlandCityToCoast, true]
-
A.
connectsCoastalCity
Indicates a relationship where one entity provides a direct connection or link (such as transport or infrastructure) between coastal cities.
-
B.
connectsPeninsulaTo
Indicates a relationship where a geographic feature or structure links a peninsula to another landmass or area.
-
C.
hasCityOnShore
Indicates that a city is located on or directly adjacent to the shore of a body of water.
-
D.
hasMaritimeConnection
Indicates a relationship in which an entity is linked to seas, oceans, or maritime activities, such as shipping, navigation, or coastal operations.
-
E.
isCoastalSettlementOf
Indicates that a settlement is located on or near the coast within the territory of a specified geographic or administrative area.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd04609748190987a9364a387fa61 |
completed | April 2, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 9 p.m.