Triple
T1367577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umm Habiba |
E30037
|
entity |
| Predicate | hadithNarrationsCountApprox |
P26982
|
FINISHED |
| Object | few dozen |
—
|
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: few dozen | Statement: [Umm Habiba, hadithNarrationsCountApprox, few dozen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadithNarrationsCountApprox Context triple: [Umm Habiba, hadithNarrationsCountApprox, few dozen]
-
A.
approximateNumberOfTractates
Indicates a relationship where an entity is associated with an estimated or non-exact count of tractates linked to it.
-
B.
hasApproximateAdherents
Indicates that an entity is associated with a non-exact, estimated number of adherents or followers.
-
C.
hasMultipleVerses
Indicates that something, typically a song, poem, or text, consists of more than one verse.
-
D.
laterAdherentsCount
Indicates the number of adherents who joined or adopted something after an initial reference point or time.
-
E.
hasMinarets
Indicates that an entity (typically a building) possesses one or more minarets as architectural features.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2d33d2081908008494b5f56bf56 |
completed | March 1, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69a4befb08b88190be966fa1aadd4bcd |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfc2134c81909cbaaa151d96e9a8 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:57 p.m.