Triple
T38546024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | That Midnight Kiss |
E924964
|
entity |
| Predicate | featuresPerformerInFirstLeadingRole |
P185143
|
FINISHED |
| Object | Mario Lanza |
E270889
|
NE 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: Mario Lanza | Statement: [That Midnight Kiss, featuresPerformerInFirstLeadingRole, Mario Lanza]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresPerformerInFirstLeadingRole Context triple: [That Midnight Kiss, featuresPerformerInFirstLeadingRole, Mario Lanza]
-
A.
featuresPerformerCameo
Indicates that the subject includes a brief, special appearance by a performer who is not part of the main cast or lineup.
-
B.
featuresPerformerType
Indicates that something includes or highlights a performer of a specified type (e.g., musician, actor, or other performance role).
-
C.
featuresPerformerAsSelfTypeRole
Indicates that a work includes a performer appearing as themselves in a specific type of role.
-
D.
featuresOnScreenPerformer
Indicates that something (such as a work or production) includes a particular performer visibly appearing on screen.
-
E.
filmStarringSinger
chosen
Indicates that a film features a singer in a starring or leading role.
- F. None of above.
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_69f76eadeac081909cdfdd0474cb6765 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41ea8a8dc0819096eb2703590afebe |
completed | June 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.