Triple
T31038118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muscadet-Sèvre et Maine |
E790905
|
entity |
| Predicate | leesContactEffect |
P66629
|
FINISHED |
| Object | adds texture |
—
|
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: adds texture | Statement: [Muscadet-Sèvre et Maine, leesContactEffect, adds texture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leesContactEffect Context triple: [Muscadet-Sèvre et Maine, leesContactEffect, adds texture]
-
A.
contactWith
Indicates that two entities are in direct or indirect physical or communicative interaction or touch with each other.
-
B.
hasContactInfluenceFrom
chosen
Indicates that one entity’s state, behavior, or properties are directly affected or altered through physical or direct contact with another entity.
-
C.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
D.
contactPhenomena
Indicates a relationship where two or more physical phenomena come into direct interaction or touch with each other.
-
E.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
- 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_69f224c97a788190b5da1ead6038a74e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f694f800e48190bad9640e6896b76b |
completed | May 3, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69f690f13d7481908ddfefe95df2a1c2 |
completed | May 3, 2026, 12:04 a.m. |
Created at: April 29, 2026, 8:59 p.m.