Triple
T38627789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Children’s Parade |
E937362
|
entity |
| Predicate | hasLocalInvolvement |
P89454
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Children’s Parade, hasLocalInvolvement, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalInvolvement Context triple: [Children’s Parade, hasLocalInvolvement, high]
-
A.
hasLocalImpact
chosen
Indicates that an entity produces effects or consequences within a specific local area or community.
-
B.
hasBeenInvolvedIn
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
C.
hasAuthorityInvolved
Indicates that an authority or official body is involved in, oversees, or has jurisdiction over the referenced situation or relationship.
-
D.
involvedTown
Indicates that a town participates in, is associated with, or is affected by a particular event, activity, or relationship.
-
E.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
- 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_69f76ed5ca3c81909288f61fbf37b359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ffe12ee59c8190bc7da386e6d5332d |
completed | May 10, 2026, 1:36 a.m. |
| PD | Predicate disambiguation | batch_69ffe0a138bc8190a3d4b48cd579e985 |
completed | May 10, 2026, 1:34 a.m. |
Created at: May 3, 2026, 4:32 p.m.