Triple
T19043717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhangi Misl |
E466073
|
entity |
| Predicate | numberOfMisls |
P134860
|
FINISHED |
| Object | one of twelve major Sikh misls |
—
|
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: one of twelve major Sikh misls | Statement: [Bhangi Misl, numberOfMisls, one of twelve major Sikh misls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMisls Context triple: [Bhangi Misl, numberOfMisls, one of twelve major Sikh misls]
-
A.
misl
Indicates a relationship where one entity is incorrectly labeled, classified, or identified as another.
-
B.
numberOfMistrialsOrUntried
Indicates the count of legal cases that either ended in a mistrial or have not yet been brought to trial.
-
C.
malaStandardCount
Indicates the number of standard units or items associated with the mala in the given context.
-
D.
numberOfMissions
Indicates the total count of missions associated with a given entity or context.
-
E.
hasNumberOfOverlooks
Indicates the specific count of overlooks (such as viewing points or vantage spots) associated with an entity.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d802a75c8190a4ce45e5fbffc1b7 |
completed | April 20, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
| PDg | Predicate description generation | batch_69e4c0fc3c4c8190abbfe06e1bd3325c |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 12:03 p.m.