Triple
T33150191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Woman from Pontus |
E848413
|
entity |
| Predicate | probableSettingRegion |
P62106
|
FINISHED |
| Object | Pontus |
—
|
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: Pontus | Statement: [The Woman from Pontus, probableSettingRegion, Pontus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: probableSettingRegion Context triple: [The Woman from Pontus, probableSettingRegion, Pontus]
-
A.
likelyRegion
chosen
Indicates that an entity is probably located in, associated with, or originates from a particular geographic region.
-
B.
regionSetting
Indicates that an entity is configured to operate within, or is associated with, a specific geographic or logical region.
-
C.
likelyLocatedIn
Indicates that an entity is probably situated within or associated with a particular location, though not with absolute certainty.
-
D.
eligibleRegion
Indicates the geographic area within which something (such as an offer, service, or rule) is valid, applicable, or permitted.
-
E.
proposedForRegion
Indicates that something has been suggested or designated to apply to, operate in, or be 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_69f3495a458c8190a1d34b237ba0be3f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:28 a.m.