Triple
T8368784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quan Am |
E197401
|
entity |
| Predicate | label |
P38
|
FINISHED |
| Object | Quan Am |
E197401
|
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: Quan Am | Statement: [Quan Am, label, Quan Am]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quan Am Context triple: [Quan Am, label, Quan Am]
-
A.
Quan Am
chosen
Quan Am is the Vietnamese name for the bodhisattva of compassion, derived from the East Asian Buddhist deity Guanyin.
-
B.
Quan
Quan is the family name of Ke Huy Quan, the Vietnamese-American actor known for roles in films like "Indiana Jones and the Temple of Doom" and "Everything Everywhere All at Once."
-
C.
Kwan
Kwan is a Chinese-origin surname shared by many individuals, including the renowned American figure skater Michelle Kwan.
-
D.
Nam Ou
Nam Ou is a significant river in northern Laos known for its scenic valleys, hydropower dams, and role in regional transport and livelihoods.
-
E.
Hoan-ya
Hoan-ya is an alternative name for the Hoanya language, an indigenous Formosan language historically spoken in Taiwan.
- 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_69ca82f56730819080cec5d991c76f4c |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb808f7c0481909fef5834cb6e7a3e |
completed | March 31, 2026, 8:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc7929e388190b35505378d0cf653 |
completed | April 2, 2026, 1:34 a.m. |
Created at: March 30, 2026, 6:01 p.m.