Triple
T3917083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LMS Black Five |
E88866
|
entity |
| Predicate | fameFor |
P52554
|
FINISHED |
| Object | versatility |
—
|
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: versatility | Statement: [LMS Black Five, fameFor, versatility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fameFor Context triple: [LMS Black Five, fameFor, versatility]
-
A.
formerlyKnownFor
Indicates that an entity was previously recognized or notable for a particular role, attribute, or activity, but is no longer primarily associated with it.
-
B.
inscriptionFamousFor
Indicates that an inscription is widely recognized or notable specifically because of the referenced feature, event, content, or characteristic.
-
C.
reconocidaPor
Indicates that an entity is recognized, acknowledged, or honored by another entity.
-
D.
fameStatus
Indicates the level or state of public recognition or renown associated with an entity.
-
E.
madeFamousByFilm
Indicates that something became widely known or gained significant public recognition as a result of being featured in a film.
- 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef18748648190b85e62f7796ff4b4 |
completed | March 9, 2026, 4:12 p.m. |
Created at: March 9, 2026, 3:22 p.m.