Triple
T28655141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lahore–Jeddah |
E725309
|
entity |
| Predicate | servesReligiousSites |
P87888
|
FINISHED |
| Object | Mecca |
—
|
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: Mecca | Statement: [Lahore–Jeddah, servesReligiousSites, Mecca]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesReligiousSites Context triple: [Lahore–Jeddah, servesReligiousSites, Mecca]
-
A.
hasReligiousSite
Indicates that a location or entity possesses, contains, or is associated with a religious site such as a temple, church, mosque, shrine, or similar place of worship.
-
B.
nearReligiousSite
Indicates that one entity is located close to or in the immediate vicinity of a religious site.
-
C.
connectsReligiousSite
chosen
Indicates a relationship where something serves as a link, route, or association between one religious site and another.
-
D.
religiousSiteInRegion
Indicates that a religious site is located within or belongs to a specified geographic region.
-
E.
religiousSiteType
Indicates the specific kind or category of religious site associated with an entity (e.g., church, mosque, temple).
- 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_69f01d84f5f0819087ab5e6143b14ed7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
Created at: April 28, 2026, 4:54 a.m.