Triple
T17784240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lighter series |
E443975
|
entity |
| Predicate | hasTitleLanguageVariant |
P15390
|
FINISHED |
| Object | Lighter |
—
|
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: Lighter | Statement: [Lighter series, hasTitleLanguageVariant, Lighter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleLanguageVariant Context triple: [Lighter series, hasTitleLanguageVariant, Lighter]
-
A.
hasTitleInLanguage
chosen
Indicates that an entity has a specific title expressed in a particular language.
-
B.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
-
C.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
D.
hasLatinTitle
Indicates that an entity possesses a title or name expressed in Latin.
-
E.
hasCensoredTitleVariant
Indicates that an entity has an alternative version of its title that has been modified or censored, typically to remove or obscure sensitive or inappropriate content.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48791dec0819090d6e88449389fc0 |
completed | April 19, 2026, 7:43 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:12 a.m.