Triple
T2526173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guru Nanak |
E56039
|
entity |
| Predicate | numberOfSuccessors |
P39357
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Guru Nanak, numberOfSuccessors, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSuccessors Context triple: [Guru Nanak, numberOfSuccessors, 9]
-
A.
successorFunction
Indicates the relationship where one entity is defined as the immediate next or following element in a sequence or ordered set relative to another.
-
B.
eventualSuccessor
Indicates that one entity will become the successor of another at some later point in time, rather than immediately.
-
C.
hasMoreAggressiveSuccessor
Indicates that one entity is followed or replaced by another entity that exhibits a higher level of aggressiveness in behavior, strategy, or effect.
-
D.
successorState
Indicates that one state directly follows another as the immediate next state in a sequence or process.
-
E.
successorLabel
Indicates that one entity is the direct successor or next in sequence to another entity, often inheriting its role, position, or label.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd255f0d081908d20cfb812c4bfc1 |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd18e72a88190bdcf12b326d42fad |
completed | March 7, 2026, 7:19 a.m. |
Created at: March 6, 2026, 9:46 p.m.