Triple
T25814388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | يثرب |
E650208
|
entity |
| Predicate | oldNameOf |
P65
|
FINISHED |
| Object | المدينة المنورة |
—
|
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: المدينة المنورة | Statement: [يثرب, oldNameOf, المدينة المنورة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oldNameOf Context triple: [يثرب, oldNameOf, المدينة المنورة]
-
A.
formerName
chosen
Indicates that an entity was previously known by a different name in the past.
-
B.
previousNameOfDate
Indicates that one date was formerly known or designated by another date, representing a prior naming or labeling of the same temporal reference.
-
C.
previousNameUsedUntil
Indicates that a particular name was used for an entity up to (but not necessarily including) a specified end date or time.
-
D.
originalNameUsedInYears
Indicates that a particular original name was in use for an entity during a specified range of years.
-
E.
wasRenamedBackTo
Indicates that an entity, after having its name changed, was later restored to its previous or original name.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f600c84ac4819091492e52a5a8b873 |
completed | May 2, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 7:12 a.m.