Triple
T4081225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibn Battuta |
E87480
|
entity |
| Predicate | numberOfHajjPilgrimages |
P26543
|
FINISHED |
| Object | at least one |
—
|
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: at least one | Statement: [Ibn Battuta, numberOfHajjPilgrimages, at least one]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHajjPilgrimages Context triple: [Ibn Battuta, numberOfHajjPilgrimages, at least one]
-
A.
numberOfPilgrimagesToMecca
chosen
Indicates the count of times an entity has undertaken a pilgrimage to Mecca.
-
B.
pilgrimageFrequency
Indicates how often an entity undertakes or participates in a pilgrimage.
-
C.
numberOfImams
Indicates the count of distinct imams associated with or relevant to a given entity or context.
-
D.
pilgrimageAssociatedWith
Indicates a relationship where a pilgrimage is connected or related to a particular entity, such as a place, person, event, or religious tradition.
-
E.
hasNumberOfMosques
Indicates the quantity of mosques associated with a given entity.
- 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_69aed9435cf48190ad1da737c962d19d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc5204d881909829de15015aa50d |
completed | March 9, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69aef9082c2081908474f082a49bebc8 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:39 p.m.