Triple
T36408872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poltergeist (2015 film) |
E896821
|
entity |
| Predicate | hasMarketingFormat |
P204163
|
FINISHED |
| Object | 3D |
—
|
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: 3D | Statement: [Poltergeist (2015 film), hasMarketingFormat, 3D]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketingFormat Context triple: [Poltergeist (2015 film), hasMarketingFormat, 3D]
-
A.
hasMarketingElement
Indicates that one entity includes, is associated with, or makes use of a particular marketing-related component or feature.
-
B.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
C.
hasMarketingDescription
Indicates that an entity is associated with a textual marketing-oriented description used to promote or present it.
-
D.
hasMarketingIcon
Indicates that an entity is associated with, or represented by, a specific marketing-related icon or symbol.
-
E.
hasMarketingPoint
Indicates that an entity possesses or is associated with a specific marketing-related feature, advantage, or talking point.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a033d975d788190aafc4be10d6c5c1c |
completed | May 12, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_6a033cc2668481908cb696e57632a68f |
completed | May 12, 2026, 2:44 p.m. |
| PDg | Predicate description generation | batch_6a033d9690e081909f65653b0dc80e20 |
completed | May 12, 2026, 2:47 p.m. |
Created at: May 3, 2026, 4:10 p.m.