Triple
T120200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Thief of Bagdad (1924 film) |
E2427
|
entity |
| Predicate | hasLegacyStatus |
P267
|
FINISHED |
| Object | landmark of silent cinema |
—
|
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: landmark of silent cinema | Statement: [The Thief of Bagdad (1924 film), hasLegacyStatus, landmark of silent cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegacyStatus Context triple: [The Thief of Bagdad (1924 film), hasLegacyStatus, landmark of silent cinema]
-
A.
hasLegacy
chosen
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
-
B.
hasLegalStatus
Indicates that an entity possesses a particular legal classification, recognition, or standing under law.
-
C.
isHistoric
Indicates that something has significant importance or relevance in history, often due to its age, impact, or role in past events.
-
D.
hasIconicStatus
Indicates that an entity holds a widely recognized, emblematic, or culturally significant status within a particular domain or context.
-
E.
hasHistoricalPrecursor
Indicates that one entity existed earlier and served as a predecessor, model, or influential forerunner to the other in a historical context.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a258fd278481908ad4498e03f38e2f |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a25647fe6081908cb0405266d35ff5 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.