Triple
T120109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mark of Zorro |
E2426
|
entity |
| Predicate | hasIntertitlesLanguage |
P7742
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [The Mark of Zorro, hasIntertitlesLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIntertitlesLanguage Context triple: [The Mark of Zorro, hasIntertitlesLanguage, English]
-
A.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
B.
presentedInLanguage
Indicates that something (such as content, information, or a work) is expressed or made available using a particular language.
-
C.
languageOfSignage
Indicates the language used on signs or written displays associated with an entity.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
includesLanguage
Indicates that one entity contains, supports, or makes use of a specified language as part of its content, functionality, or representation.
- 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_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. |
| PDg | Predicate description generation | batch_69a258fbd18881908c9d40f7a2480945 |
completed | Feb. 28, 2026, 2:54 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.