Triple
T34791788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard |
E1002966
|
entity |
| Predicate | hasNameUsageType |
P12827
|
FINISHED |
| Object | personal given name |
—
|
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: personal given name | Statement: [Howard, hasNameUsageType, personal given name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameUsageType Context triple: [Howard, hasNameUsageType, personal given name]
-
A.
hasNameEntityUsage
Indicates that an entity is associated with a particular usage or occurrence of a specific name.
-
B.
hasGivenNameUsage
chosen
Indicates that an entity is associated with a particular way or context in which its given name is used.
-
C.
hasNameOriginType
Indicates that there is a specific type or category describing the origin of an entity’s name.
-
D.
hasNameUsageCountry
Indicates that a particular name is used or recognized within a specified country.
-
E.
hasTypeName
Indicates that an entity is associated with a specific type name used to classify or identify its kind.
- 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_69f76db47d408190a24fc7164439ea2d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff246e0d4481908bcec718e1d4025b |
completed | May 9, 2026, 12:11 p.m. |
| PD | Predicate disambiguation | batch_69ff23cb70ac81909b776ace4597ae9c |
completed | May 9, 2026, 12:08 p.m. |
Created at: May 3, 2026, 3:59 p.m.