Triple
T37216611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mecidiye |
E922754
|
entity |
| Predicate | hasToponymicContinuityWith |
P144466
|
FINISHED |
| Object | Medgidia |
—
|
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: Medgidia | Statement: [Mecidiye, hasToponymicContinuityWith, Medgidia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToponymicContinuityWith Context triple: [Mecidiye, hasToponymicContinuityWith, Medgidia]
-
A.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
B.
hasToponymicDerivatives
Indicates that a name or term serves as the source from which related place-based or toponymic names are derived.
-
C.
legacyToponym
chosen
Indicates that one place name is an older or former name historically used to refer to the same geographic entity as another place name.
-
D.
isToponymOf
Indicates that one entity is a place name (toponym) that refers to the location represented by the other entity.
-
E.
hasToponymicAssociation
Indicates a relationship where one entity is associated with, derived from, or named after a particular place or geographic name (toponym).
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd7e364a648190a1e9e1d9fc76e99e |
completed | May 8, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69fd7bb547608190a3b04dddbca6b8bc |
completed | May 8, 2026, 5:59 a.m. |
Created at: May 3, 2026, 4:15 p.m.