Triple
T36346052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Seine à Pont-de-l'Arche |
E895066
|
entity |
| Predicate | subjectLocationRegion |
P64798
|
FINISHED |
| Object | Normandy |
—
|
NE NERFINISHED |
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: Normandy | Statement: [La Seine à Pont-de-l'Arche, subjectLocationRegion, Normandy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectLocationRegion Context triple: [La Seine à Pont-de-l'Arche, subjectLocationRegion, Normandy]
-
A.
subjectLocation
Indicates that one entity is located at, in, or near the place or position specified by another entity.
-
B.
placeRegion
chosen
Indicates that a place is located within, or is part of, a larger geographic or administrative region.
-
C.
socialRegionFor
Indicates a relationship where a social entity (such as a group, community, or organization) is associated with or operates within a particular geographic or social region.
-
D.
subjectLocationType
Indicates the type or category of location associated with the subject in the relationship.
-
E.
regionFrom
Indicates that something originates from, is derived from, or is associated with a particular geographic or administrative region.
- 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_69f76e4f437c8190a1af3ea2564f41f5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 3, 2026, 4:09 p.m.