Triple
T3276965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moana |
E68779
|
entity |
| Predicate | characterIn |
P12208
|
FINISHED |
| Object | Sina |
E318539
|
NE 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: Sina | Statement: [Moana, characterIn, Sina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sina Context triple: [Moana, characterIn, Sina]
-
A.
Sina
chosen
Sina is a given name and surname used in various cultures, often associated with notable figures in fields such as science, arts, and media.
-
B.
Shina
Shina is an Indo-Aryan language spoken primarily in the Gilgit-Baltistan region of Pakistan and surrounding Himalayan areas.
-
C.
Tsien
Tsien is a Chinese surname borne by several notable figures in science and engineering, including biophysicist Richard Tsien.
-
D.
Tsinan
Tsinan is an older romanized name for Jinan, the capital city of Shandong Province in eastern China known for its numerous natural springs.
-
E.
Hui
The Hui are a predominantly Muslim ethnic group in China known for their integration of Islamic faith with Han Chinese language and cultural practices.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0128f08819084644f3c8fda2596 |
completed | March 8, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e84a3c2c8190908152fc042fcad1 |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:10 p.m.