Triple
T23860078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MF |
E592420
|
entity |
| Predicate | introducedForEntity |
P154218
|
FINISHED |
| Object | Saint Martin (French part) |
—
|
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: Saint Martin (French part) | Statement: [MF, introducedForEntity, Saint Martin (French part)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedForEntity Context triple: [MF, introducedForEntity, Saint Martin (French part)]
-
A.
introducedFor
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
B.
introducedForModel
Indicates that one entity was created, proposed, or brought into use specifically for application within a particular model.
-
C.
introducedForState
Indicates that something was created, proposed, or brought forward specifically for use in or application to a particular state.
-
D.
introducedForServiceWith
Indicates that one entity was presented or brought to the attention of another entity specifically for the purpose of providing a service.
-
E.
settingIntroducedIn
Indicates the work, installment, or context in which a particular setting first appears or is established.
- 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_69e25d22eb488190914b193aff952e83 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cadebc6481909110a2a5fe85c93f |
completed | April 29, 2026, 9:09 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 8:12 p.m.