Triple
T16783455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frameries |
E407910
|
entity |
| Predicate | hasINSEECityCode |
P7614
|
FINISHED |
| Object | 53028 |
—
|
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: 53028 | Statement: [Frameries, hasINSEECityCode, 53028]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasINSEECityCode Context triple: [Frameries, hasINSEECityCode, 53028]
-
A.
hasINSEECODE
chosen
Indicates that an entity is associated with a specific INSEE code, identifying it within the French national statistical and administrative system.
-
B.
isInCity
Indicates that one entity is located within the geographical boundaries of a specified city.
-
C.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
-
D.
hasMetropolitanCityCode
Indicates that an entity is associated with a specific metropolitan city identified by a standardized code.
-
E.
hasInlandCity
Indicates that one entity has, contains, or is associated with a city located inland (away from the coast or major bodies of water).
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b218d31881908d896e688ebd171c |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.