Triple
T1289434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dhu al-Hijjah |
E27510
|
entity |
| Predicate | hasFirstTenDaysVirtue |
P28134
|
FINISHED |
| Object | highly meritorious for worship in Islam |
—
|
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: highly meritorious for worship in Islam | Statement: [Dhu al-Hijjah, hasFirstTenDaysVirtue, highly meritorious for worship in Islam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstTenDaysVirtue Context triple: [Dhu al-Hijjah, hasFirstTenDaysVirtue, highly meritorious for worship in Islam]
-
A.
hasDays
Indicates that an entity is associated with, spans, or occurs on specific days.
-
B.
hasNumberOfTemptations
Indicates the specific count of temptations associated with an entity or situation.
-
C.
hasFirstTrial
Indicates that an entity is associated with its initial or earliest trial, test, or legal proceeding.
-
D.
hasHonorPrinciple
Indicates that an entity adheres to or is guided by a specific principle related to honor or honorable conduct.
-
E.
hasCredit
Indicates that an entity possesses or is assigned a credit, such as financial credit, academic credit, or acknowledgment for a contribution.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d4dfb081908c8825d6062b1d99 |
completed | March 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69a4bee41ca08190b0ad6f7ea40c0b62 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bfa205ec81909d8170b398345615 |
completed | March 1, 2026, 10:37 p.m. |
Created at: March 1, 2026, 7:51 p.m.