Triple
T18177212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allen Ludden |
E435193
|
entity |
| Predicate | hasSignatureGlasses |
P106954
|
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: [Allen Ludden, hasSignatureGlasses, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignatureGlasses Context triple: [Allen Ludden, hasSignatureGlasses, yes]
-
A.
hasEyeWear
Indicates that one entity is wearing or equipped with some form of eyewear (such as glasses, goggles, or similar eye accessories).
-
B.
hasSignatureEquipment
chosen
Indicates that an entity is associated with a distinctive or characteristic piece of equipment that is uniquely or notably linked to it.
-
C.
has3DGlasses
Indicates that an entity possesses or is equipped with 3D glasses.
-
D.
hasInsigniaWornBy
Indicates that a particular insignia is worn by a specified entity (such as a person, group, or organization).
-
E.
hasSignatureSmile
Indicates that an entity is characterized by a distinctive or recognizable smile that serves as a notable or identifying feature.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df5a72008190bd2e56205b995a87 |
completed | April 19, 2026, 1:57 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.