Triple
T31854573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Kidville |
E813155
|
entity |
| Predicate | commonElements |
P137176
|
FINISHED |
| Object | playgrounds |
—
|
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: playgrounds | Statement: [Town of Kidville, commonElements, playgrounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonElements Context triple: [Town of Kidville, commonElements, playgrounds]
-
A.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
-
B.
commonFor
Indicates that something is typical, usual, or frequently occurring for a given entity or context.
-
C.
commonOn
Indicates that two or more entities share the same location, context, or medium where they are present or occur together.
-
D.
hasCommonElement
chosen
Indicates that two sets, collections, or groups share at least one element in common.
-
E.
commonBasis
Indicates that two or more entities share an underlying foundation, principle, or set of assumptions that supports or explains their relationship.
- 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_69f348ebf32881908d9439646933dc76 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
Created at: April 30, 2026, 11:52 p.m.