Triple
T1324410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Safa |
E28291
|
entity |
| Predicate | sa'iDirection |
P24810
|
FINISHED |
| Object | from al-Safa to al-Marwah |
—
|
LITERAL FINISHED |
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: from al-Safa to al-Marwah | Statement: [al-Safa, sa'iDirection, from al-Safa to al-Marwah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sa'iDirection Context triple: [al-Safa, sa'iDirection, from al-Safa to al-Marwah]
-
A.
servesDirection
Indicates that one entity provides service or functionality oriented toward, or in the direction of, another entity.
-
B.
containsDirectionOf
Indicates that one entity includes or encompasses the directional orientation or path associated with another entity.
-
C.
via
Indicates that something occurs, is achieved, or is connected by means of, through the use of, or along the route of another entity or medium.
-
D.
transportDirection
chosen
Indicates the directional flow or route along which something is transported from an origin toward a destination.
-
E.
SakaeIs
Indicates that one entity is identified as or classified as "Sakae" in relation to another entity or context.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19e81c0819092f85201ae34422a |
completed | March 1, 2026, 10:45 p.m. |
| PD | Predicate disambiguation | batch_69a4beedb49c8190beb5b85cdda05013 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.