Triple
T36273581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinmel |
E892740
|
entity |
| Predicate | mosqueInfluenceOn |
P186426
|
FINISHED |
| Object | Kutubiyya Mosque in Marrakesh |
E137888
|
NE 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: Kutubiyya Mosque in Marrakesh | Statement: [Tinmel, mosqueInfluenceOn, Kutubiyya Mosque in Marrakesh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mosqueInfluenceOn Context triple: [Tinmel, mosqueInfluenceOn, Kutubiyya Mosque in Marrakesh]
-
A.
mosqueFunction
Indicates that one entity serves as the religious or communal function or role of a mosque for another entity.
-
B.
hasMosque
Indicates that one entity possesses, contains, or is the location of a mosque.
-
C.
associatedWithMosque
Indicates a relationship where an entity has a connection or affiliation with a mosque, such as through location, use, administration, or religious function.
-
D.
mosqueBuiltUnder
Indicates that a mosque was constructed during the rule, authority, or administration of a particular person, group, or regime.
-
E.
hasNumberOfMosques
Indicates the quantity of mosques associated with a given entity.
- F. None of above. chosen
Provenance (5 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_69f76e488f34819083e254dbe288c27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a396e13639881909ca61dd0d92a5932 |
completed | June 22, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7cec398ac819081c954a993c323ee |
completed | May 3, 2026, 10:40 p.m. |
Created at: May 3, 2026, 4:09 p.m.