Triple
T28295808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Dishman |
E713566
|
entity |
| Predicate | hasNameEntityUsage |
P191780
|
FINISHED |
| Object | eponym of a public community center |
—
|
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: eponym of a public community center | Statement: [Matt Dishman, hasNameEntityUsage, eponym of a public community center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameEntityUsage Context triple: [Matt Dishman, hasNameEntityUsage, eponym of a public community center]
-
A.
hasGivenNameUsage
Indicates that an entity is associated with a particular way or context in which its given name is used.
-
B.
hasFullNameUsage
Indicates that an entity uses a particular full name in a specific context or manner.
-
C.
isNamedEntity
Indicates that the subject is recognized as a named entity, such as a specific person, organization, location, or other proper noun.
-
D.
incorrectInformalUsageOfName
Indicates that one entity uses another entity’s name in an informal context in a way that is considered incorrect or inappropriate.
-
E.
hasNameUsageCountry
Indicates that a particular name is used or recognized within a specified country.
- 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_69efb524ab688190a1ce7ee7c9520932 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
| PDg | Predicate description generation | batch_69fcec5e560481909cd710b88897e833 |
completed | May 7, 2026, 7:47 p.m. |
Created at: April 27, 2026, 11:32 p.m.