Triple
T201041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Rooney |
E4503
|
entity |
| Predicate | notableFact |
P8229
|
FINISHED |
| Object | career spanned nine decades |
—
|
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: career spanned nine decades | Statement: [Mickey Rooney, notableFact, career spanned nine decades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFact Context triple: [Mickey Rooney, notableFact, career spanned nine decades]
-
A.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
B.
notableSingle
Indicates that the subject is particularly recognized or distinguished for one specific, individual instance (such as a single work, event, or achievement).
-
C.
notablePrimary
Indicates that one entity is the main or most prominent example, instance, or representative of another entity.
-
D.
notableCategory
Indicates that an entity is recognized as notable or significant within a particular category or classification.
-
E.
notableStory
Indicates that an entity is the subject or source of a story, account, or narrative that is considered notable or significant.
- F. None of above. chosen
Provenance (4 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c2ead8481909996042efcae5e9d |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b4a0d448190a6fa6aeb30dc7e13 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25c2bda788190bcfc0bc94686f9e0 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.