Triple
T36563354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Harding |
E901902
|
entity |
| Predicate | hasAmbiguityReason |
P88916
|
FINISHED |
| Object | common combination of given name Robert and surname Harding |
—
|
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: common combination of given name Robert and surname Harding | Statement: [Robert Harding, hasAmbiguityReason, common combination of given name Robert and surname Harding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAmbiguityReason Context triple: [Robert Harding, hasAmbiguityReason, common combination of given name Robert and surname Harding]
-
A.
hasAmbiguous
Indicates that the relationship or state is unclear, uncertain, or open to multiple interpretations.
-
B.
hasUncertaintyReason
chosen
Indicates that there is a specific reason or explanation for why something is uncertain or not known with confidence.
-
C.
isAmbiguousIn
Indicates that something has multiple possible interpretations or meanings within a given context, making its intended sense unclear.
-
D.
hasAmbiguousIdentity
Indicates that an entity’s identity is unclear, uncertain, or can be interpreted in multiple distinct ways.
-
E.
hasAmbiguousEnding
Indicates that the event, story, or situation concludes in a way that is open to multiple interpretations or lacks a clear, definitive resolution.
- 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_69f76e634e9481908c9ba1b87ab87c26 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.