Triple
T21685457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadiqat al-Haqiqa |
E535217
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Sanai |
—
|
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: Sanai | Statement: [Hadiqat al-Haqiqa, author, Sanai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanai Context triple: [Hadiqat al-Haqiqa, author, Sanai]
-
A.
Sana'i
chosen
Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
-
B.
Artsyz
Artsyz is a small town in southwestern Ukraine known for its agricultural surroundings and location within the historical region of Bessarabia.
-
C.
Sanhe
Sanhe is a county-level city in northern China’s Hebei province, administered by the prefecture-level city of Langfang near the Beijing–Tianjin region.
-
D.
Tejen
Tejen is a city in southern Turkmenistan known as an agricultural and transport hub near the border with Iran.
-
E.
Sani
Sani is a subgroup of the Yi ethnic people in China, known for their distinct language, traditional dress, and rich folk culture.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96ca668481909f53853c7a8ea811 |
completed | April 27, 2026, 5:03 p.m. |
Created at: April 16, 2026, 6:44 p.m.