Triple
T33514273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Harra |
E858323
|
entity |
| Predicate | nearbyHolyCity |
P29505
|
FINISHED |
| Object | Medina |
—
|
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: Medina | Statement: [al-Harra, nearbyHolyCity, Medina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyHolyCity Context triple: [al-Harra, nearbyHolyCity, Medina]
-
A.
holyCityFor
Indicates that a city holds recognized religious significance or sacred status for a particular religion or religious community.
-
B.
holyCityAlongWith
Indicates that one entity is recognized or designated as a holy city together with, or in association with, another entity.
-
C.
nearReligiousSite
chosen
Indicates that one entity is located close to or in the immediate vicinity of a religious site.
-
D.
religiousTextAssociationNearby
Indicates a spatial relationship where a religious text or related object is located close to or in the immediate vicinity of another entity.
-
E.
nearbyTraditionalCapital
Indicates that one location is geographically close to a place that serves or served as a traditional capital.
- 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_69f3497721848190978fbee5e0a526f8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe163a41a0819098403b470e327d29 |
completed | May 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fe1358db5c819092570814a37ef5bd |
completed | May 8, 2026, 4:46 p.m. |
Created at: May 1, 2026, 1:39 a.m.