Triple
T22704993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lahore District |
E561425
|
entity |
| Predicate | hasCulturalSite |
P1098
|
FINISHED |
| Object | Data Darbar |
—
|
NE NERFINISHED |
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: Data Darbar | Statement: [Lahore District, hasCulturalSite, Data Darbar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Data Darbar Context triple: [Lahore District, hasCulturalSite, Data Darbar]
-
A.
Data Darbar
chosen
Data Darbar is one of South Asia’s largest and most famous Sufi shrines, dedicated to the revered saint Data Ganj Bakhsh in Lahore, Pakistan.
-
B.
Data Ganj Bakhsh Shrine
Data Ganj Bakhsh Shrine is a major Sufi mausoleum and pilgrimage site in Lahore, Pakistan, dedicated to the revered Persian Sufi saint Ali Hujwiri.
-
C.
Data Ganjbakhsh
Data Ganjbakhsh is a renowned 11th-century Persian Sufi saint and scholar whose shrine in Lahore is a major center of spiritual devotion in South Asia.
-
D.
Dorbar
Dorbar is the traditional village council and grassroots governance institution of the Khasi people in northeastern India.
-
E.
Nizamat Imambara
Nizamat Imambara is a grand 19th-century Shia congregation hall and one of the largest imambaras in India, located in Murshidabad, West Bengal.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178cdc93481908f85d04560f8c285 |
completed | April 29, 2026, 3:19 a.m. |
Created at: April 17, 2026, 3:16 p.m.