Triple
T30567559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander the Great (1979 film) |
E778026
|
entity |
| Predicate | hasPoliticalAllegory |
P195684
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Alexander the Great (1979 film), hasPoliticalAllegory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliticalAllegory Context triple: [Alexander the Great (1979 film), hasPoliticalAllegory, true]
-
A.
politicalAllegoryFor
Indicates that one entity symbolically represents or critiques another entity, event, or system within a political context.
-
B.
allegoricalInterpretation
Indicates that one entity is interpreted as symbolically representing deeper, often moral or spiritual, meanings within another entity (such as a text, image, or event).
-
C.
hasAllegoricalDepictionsBy
Indicates that one entity is represented through allegorical depictions created by another entity.
-
D.
hasAllegoricalFigures
Indicates that a work, scene, or element includes figures that symbolically represent abstract ideas, concepts, or moral qualities.
-
E.
containsAllusion
Indicates that one entity includes or incorporates an indirect reference or allusion to another entity.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
| PDg | Predicate description generation | batch_69fddf70ab10819088b76bd98e208354 |
completed | May 8, 2026, 1:04 p.m. |
Created at: April 29, 2026, 8:21 p.m.