Triple
T24430217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Lachey |
E615981
|
entity |
| Predicate | correspondentFor |
P156089
|
FINISHED |
| Object | Entertainment Tonight |
—
|
NE NERFINISHED |
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: Entertainment Tonight | Statement: [Vanessa Lachey, correspondentFor, Entertainment Tonight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondentFor Context triple: [Vanessa Lachey, correspondentFor, Entertainment Tonight]
-
A.
notableCorrespondent
Indicates that one entity is a significant or distinguished correspondent of another, typically through notable or historically important exchanges of communication.
-
B.
correspondenceRelationshipWith
Indicates a relationship in which two entities are connected through the exchange or maintenance of correspondence (such as letters, messages, or other communications).
-
C.
addresseeOf
Indicates that one entity is the intended recipient or target audience of a communication, message, or expression from another entity.
-
D.
representedFor
Indicates that one entity has acted or served as the official representative or proxy on behalf of another entity.
-
E.
correspondedWith
Indicates that two entities engaged in mutual communication, typically by exchanging messages or letters over a period of time.
- 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_69e2d7eadb248190a867130fe45f0388 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f296aab8948190b9cb869bab71fb4c |
completed | April 29, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:15 a.m.