Triple
T4901572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Adams |
E109808
|
entity |
| Predicate | disambiguationNeededInContext |
P38403
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Michael Adams, disambiguationNeededInContext, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disambiguationNeededInContext Context triple: [Michael Adams, disambiguationNeededInContext, yes]
-
A.
languageAmbiguity
Indicates that the meaning, interpretation, or reference of a linguistic expression is unclear or can be understood in multiple ways.
-
B.
hasDisambiguationPage
chosen
Indicates that there exists a disambiguation page used to distinguish between multiple entities or meanings associated with the same term.
-
C.
disputedInterpretation
Indicates that there is disagreement or contention over how something should be understood, interpreted, or explained.
-
D.
viewOnAmbiguity
Indicates an entity’s stance or attitude toward ambiguity, such as how much uncertainty or vagueness it accepts or prefers.
-
E.
oftenConfusedWith
Indicates that one entity is frequently mistaken for or thought to be another due to similarity or ambiguity.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:28 p.m.