Triple
T24888969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Levenstein |
E622940
|
entity |
| Predicate | hasEmbarrassingIncident |
P152793
|
FINISHED |
| Object | webcam incident with Nadia |
—
|
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: webcam incident with Nadia | Statement: [Jim Levenstein, hasEmbarrassingIncident, webcam incident with Nadia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmbarrassingIncident Context triple: [Jim Levenstein, hasEmbarrassingIncident, webcam incident with Nadia]
-
A.
notableGaffe
Indicates that an entity is known for having made a significant mistake, blunder, or embarrassing error.
-
B.
madePublicConfessionAt
Indicates that an entity openly admitted or confessed something in a public setting at a specific time or place.
-
C.
hasMisadventures
chosen
Indicates that an entity experiences or is involved in a series of troublesome, chaotic, or comically unfortunate events.
-
D.
hasAffairWith
Indicates that one entity is engaged in a secret or illicit romantic or sexual relationship with another entity, typically outside a committed partnership.
-
E.
hasNotableIncident
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
- 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_69e2fac597708190a922bf39a49ec70a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442b8479c8190a7c8e416ac9e28a0 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 5:25 a.m.