Triple
T38476962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slums |
E915573
|
entity |
| Predicate | supportsPublicMatches |
P204675
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Slums, supportsPublicMatches, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsPublicMatches Context triple: [Slums, supportsPublicMatches, true]
-
A.
supportsMatching
Indicates that one entity provides assistance, resources, or functionality that aligns with or complements another entity’s specific requirements or characteristics.
-
B.
supportsMultipleMatches
Indicates that the relationship or operation can involve or return more than one matching counterpart rather than being limited to a single match.
-
C.
supportsExactMatch
Indicates that one entity fully upholds or is compatible with another entity only when there is an exact, unaltered match between them.
-
D.
supportsHomeMatchesOf
Indicates that one entity provides backing, resources, or assistance specifically for the home matches of another entity.
-
E.
supportsPartialMatch
Indicates that the relationship or operation allows matching based on a subset or portion of the target criteria rather than requiring a complete or exact match.
- 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:31 p.m.