Triple
T592299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robart |
E17301
|
entity |
| Predicate | hasNameStatus |
P12717
|
FINISHED |
| Object | less common variant of Robert |
—
|
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: less common variant of Robert | Statement: [Robart, hasNameStatus, less common variant of Robert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameStatus Context triple: [Robart, hasNameStatus, less common variant of Robert]
-
A.
hasStatusLabel
chosen
Indicates that an entity is associated with a specific status expressed as a human-readable label.
-
B.
hasGivenNameUsage
Indicates that an entity is associated with a particular way or context in which its given name is used.
-
C.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
D.
nameOf
Indicates that one entity is the name or designation of another entity.
-
E.
hasIconicStatus
Indicates that an entity holds a widely recognized, emblematic, or culturally significant status within a particular domain or context.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bbaf53081908eed240bed09f63b |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cc13988190892ca10bd7ae9f09 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.