Triple
T37726542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gurdwara Bala Sahib, Delhi |
E940035
|
entity |
| Predicate | languageOfScriptureRecitation |
P142456
|
FINISHED |
| Object | Gurmukhi |
—
|
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: Gurmukhi | Statement: [Gurdwara Bala Sahib, Delhi, languageOfScriptureRecitation, Gurmukhi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfScriptureRecitation Context triple: [Gurdwara Bala Sahib, Delhi, languageOfScriptureRecitation, Gurmukhi]
-
A.
hasLanguageOfScripture
Indicates that an entity’s scriptural or sacred texts are written or expressed in a specified language.
-
B.
languageOfScripturalTradition
chosen
Indicates the language in which a given scriptural or religious textual tradition is expressed or transmitted.
-
C.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
D.
recognizesScripturesFrom
Indicates that one entity acknowledges or accepts certain scriptures as authoritative or valid based on another entity as their source or origin.
-
E.
languageOfScriptPromoted
Indicates that a particular language is associated with and promoted through the use of a given writing script.
- 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_69f76edefd048190a32212c5c3919531 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a01a819644c819094c58d083d525da0 |
completed | May 11, 2026, 9:57 a.m. |
| PD | Predicate disambiguation | batch_6a01a5dfd628819083c032d8cfd2e726 |
completed | May 11, 2026, 9:48 a.m. |
Created at: May 3, 2026, 4:18 p.m.