Triple
T4762801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shompen language |
E105735
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object |
Shom Peng
Shom Peng is an indigenous language spoken by the Shompen people of Great Nicobar Island in India’s Nicobar Islands.
|
E466989
|
NE FINISHED |
How this triple was built (4 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: Shom Peng | Statement: [Shompen language, alternativeName, Shom Peng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shom Peng Context triple: [Shompen language, alternativeName, Shom Peng]
-
A.
Pak Yong
Pak Yong is a stock male character in the traditional Malay dance-drama Mak Yong, often portrayed as a comic or supporting figure.
-
B.
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.
-
C.
Kwang-chou
Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
-
D.
Ban Pong
Ban Pong is a town in western Thailand that served as a key rail junction and starting point for the World War II–era Burma Railway.
-
E.
Shuheng
Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Shom Peng Triple: [Shompen language, alternativeName, Shom Peng]
Generated description
Shom Peng is an indigenous language spoken by the Shompen people of Great Nicobar Island in India’s Nicobar Islands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shom Peng Target entity description: Shom Peng is an indigenous language spoken by the Shompen people of Great Nicobar Island in India’s Nicobar Islands.
-
A.
Pak Yong
Pak Yong is a stock male character in the traditional Malay dance-drama Mak Yong, often portrayed as a comic or supporting figure.
-
B.
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.
-
C.
Kwang-chou
Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
-
D.
Ban Pong
Ban Pong is a town in western Thailand that served as a key rail junction and starting point for the World War II–era Burma Railway.
-
E.
Shuheng
Shuheng is the given name of He Shuheng, an early Chinese Communist revolutionary and political figure.
- F. None of above. chosen
Provenance (5 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd651091cc81909b835439c85e842f |
completed | March 20, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a81c9dc8190b9e7f399ac1de268 |
completed | March 21, 2026, 6:28 a.m. |
| NEDg | Description generation | batch_69be3b4791008190ba3f3f6e7698146f |
completed | March 21, 2026, 6:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be3bbe432081909bf134e1be799b58 |
completed | March 21, 2026, 6:33 a.m. |
Created at: March 20, 2026, 1:20 p.m.