Triple
T33873269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colin Farrell as Tommy Sweet |
E868281
|
entity |
| Predicate | hasFameStatus |
P27257
|
FINISHED |
| Object | mainstream star |
—
|
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: mainstream star | Statement: [Colin Farrell as Tommy Sweet, hasFameStatus, mainstream star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFameStatus Context triple: [Colin Farrell as Tommy Sweet, hasFameStatus, mainstream star]
-
A.
fameStatus
chosen
Indicates the level or state of public recognition or renown associated with an entity.
-
B.
basedOnFameFrom
Indicates that something is determined, influenced, or derived from the level or source of fame associated with an entity.
-
C.
fameFor
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
D.
inUniverseFame
Indicates that an entity is famous or widely recognized within the fictional universe or narrative world it belongs to.
-
E.
isMoreFamousThan
Indicates that one entity is better known or more widely recognized by people than another entity.
- 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_69f34995029081909ede0f7df73d1a5e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd7b0503a08190ba07338365b6fcc9 |
completed | May 8, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69fd7a9733dc81909199f453c0cc2bc1 |
completed | May 8, 2026, 5:54 a.m. |
Created at: May 1, 2026, 1:47 a.m.