Triple
T22944776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José García |
E569833
|
entity |
| Predicate | isAmbiguousAs |
P71696
|
FINISHED |
| Object | reference to many different persons |
—
|
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: reference to many different persons | Statement: [José García, isAmbiguousAs, reference to many different persons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAmbiguousAs Context triple: [José García, isAmbiguousAs, reference to many different persons]
-
A.
hasAmbiguous
Indicates that the relationship or state is unclear, uncertain, or open to multiple interpretations.
-
B.
isAmbiguousName
chosen
Indicates that a name can refer to multiple distinct entities or interpretations, making its reference unclear without additional context.
-
C.
hasAmbiguousEnding
Indicates that the event, story, or situation concludes in a way that is open to multiple interpretations or lacks a clear, definitive resolution.
-
D.
hasAmbiguousIdentity
Indicates that an entity’s identity is unclear, uncertain, or can be interpreted in multiple distinct ways.
-
E.
isAmbiguousWithinUSStates
Indicates that the referenced item has multiple possible interpretations or matches when considered across U.S. states, and thus cannot be uniquely associated with a single state 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1819c696c8190977bd2bca01509bc |
completed | April 29, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:45 p.m.