Triple
T1416357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John F. Kennedy Memorial |
E31925
|
entity |
| Predicate | hasStepCount |
P7664
|
FINISHED |
| Object | approximately 50 steps |
—
|
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: approximately 50 steps | Statement: [John F. Kennedy Memorial, hasStepCount, approximately 50 steps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStepCount Context triple: [John F. Kennedy Memorial, hasStepCount, approximately 50 steps]
-
A.
hasStep
Indicates that one entity includes, is composed of, or is associated with a specific step or stage in a process involving another entity.
-
B.
movementCount
Indicates the number of times a movement or relocation action has occurred between the related entities.
-
C.
hasHeadCount
Indicates that an entity is associated with a specific number of individuals, typically representing the size or count of people (or similar units) related to it.
-
D.
hasStepchildren
Indicates that one person has stepchildren, meaning children of their spouse or partner from a previous relationship.
-
E.
hasTotalNumber
chosen
Indicates that an entity is associated with a specific overall count or sum of items, elements, or units.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c403ccdc8190b2a5fda037b6ea34 |
completed | March 1, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.