Triple
T30819243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Hajar al-Aswad corner |
E784870
|
entity |
| Predicate | roleInTawaf |
P200409
|
FINISHED |
| Object | starting point of circumambulation |
—
|
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: starting point of circumambulation | Statement: [al-Hajar al-Aswad corner, roleInTawaf, starting point of circumambulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInTawaf Context triple: [al-Hajar al-Aswad corner, roleInTawaf, starting point of circumambulation]
-
A.
roleInUmrah
Indicates the specific function, duty, or position an entity holds within the context of performing or organizing Umrah.
-
B.
roleInHajj
Indicates the specific function, duty, or position an entity holds within the context of performing or organizing the Hajj pilgrimage.
-
C.
roleInMecca
Indicates that an entity holds or performs a specific role, function, or position in the context of Mecca.
-
D.
performsHajjTawaf
Indicates that an entity carries out the ritual circumambulation (tawaf) around the Kaaba as part of performing the Hajj pilgrimage.
-
E.
performsUmrahTawaf
Indicates that an entity carries out the ritual circumambulation (tawaf) around the Kaaba as part of performing Umrah.
- F. None of above. chosen
Provenance (4 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff891e4b9c8190aa86a339a8944496 |
completed | May 9, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69ff8801180c8190b23e20996ca68e0a |
completed | May 9, 2026, 7:16 p.m. |
| PDg | Predicate description generation | batch_69ff891d54248190be8742197564605a |
completed | May 9, 2026, 7:21 p.m. |
Created at: April 29, 2026, 8:44 p.m.