Triple
T35328383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Male |
E1020253
|
entity |
| Predicate | hasAdvertisingFace |
P68438
|
FINISHED |
| Object | model Tanel Derard |
—
|
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: model Tanel Derard | Statement: [Le Male, hasAdvertisingFace, model Tanel Derard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdvertisingFace Context triple: [Le Male, hasAdvertisingFace, model Tanel Derard]
-
A.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
-
B.
hasAdvertisingVisual
chosen
Indicates that an entity includes, is associated with, or uses a specific visual element or asset for advertising purposes.
-
C.
hasFacialProfile
Indicates that an entity possesses a specific facial profile or configuration of facial features.
-
D.
hasAdvertisingMarket
Indicates that an entity participates in or is associated with a specific advertising market where advertising space, time, or services are bought and sold.
-
E.
hasFaceDetectionAF
Indicates that an entity supports or uses autofocus functionality based on detecting human faces in the frame.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fdec5ffe088190ac5505f26c6cff18 |
completed | May 8, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69fdeae15f1c81908fc63fbc1b028d2e |
completed | May 8, 2026, 1:53 p.m. |
Created at: May 3, 2026, 4:03 p.m.