Triple
T37803610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gold Diggers of 1935 |
E942445
|
entity |
| Predicate | featuresNumber |
P80690
|
FINISHED |
| Object | Lullaby of Broadway |
E542183
|
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: Lullaby of Broadway | Statement: [Gold Diggers of 1935, featuresNumber, Lullaby of Broadway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresNumber Context triple: [Gold Diggers of 1935, featuresNumber, Lullaby of Broadway]
-
A.
featuresIn
chosen
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
B.
featuresDemon
Indicates that an entity includes, depicts, or prominently involves a demon.
-
C.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
-
D.
featuresSample
Indicates that an entity includes or presents a particular sample as one of its components or examples.
-
E.
featuresModel
Indicates that one entity includes, exposes, or is characterized by a particular model as one of its defining components or capabilities.
- 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_69f76ee8104c8190ab17133ccd8f86e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40f18b9750819088ffd19b4731e1ef |
completed | June 28, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.