Triple
T9051694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pearic |
E216898
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Samre
Samre is an ethnic group and language of mainland Southeast Asia, traditionally associated with the Pearic branch of the Austroasiatic language family.
|
E775506
|
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: Samre | Statement: [Pearic, hasMember, Samre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samre Context triple: [Pearic, hasMember, Samre]
-
A.
Sima Samar
Sima Samar is an Afghan physician and human rights advocate renowned for her work promoting women's rights, education, and social justice in Afghanistan.
-
B.
Samala
Samala is a small settlement located in the Río Hurtado area of northern Chile, known for its rural Andean landscape and traditional agricultural lifestyle.
-
C.
Samrat
Samrat is a person known primarily as the child of Razzak.
-
D.
Borom Sarret
Borom Sarret is a pioneering 1963 Senegalese short film by Ousmane Sembène, often regarded as one of the first works of African cinema to depict postcolonial urban life from an African perspective.
-
E.
Simuka
Simuka was the founder and one of the earliest known kings of the Satavahana dynasty in ancient India.
- 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: Samre Triple: [Pearic, hasMember, Samre]
Generated description
Samre is an ethnic group and language of mainland Southeast Asia, traditionally associated with the Pearic branch of the Austroasiatic language family.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samre Target entity description: Samre is an ethnic group and language of mainland Southeast Asia, traditionally associated with the Pearic branch of the Austroasiatic language family.
-
A.
Sima Samar
Sima Samar is an Afghan physician and human rights advocate renowned for her work promoting women's rights, education, and social justice in Afghanistan.
-
B.
Samala
Samala is a small settlement located in the Río Hurtado area of northern Chile, known for its rural Andean landscape and traditional agricultural lifestyle.
-
C.
Samrat
Samrat is a person known primarily as the child of Razzak.
-
D.
Borom Sarret
Borom Sarret is a pioneering 1963 Senegalese short film by Ousmane Sembène, often regarded as one of the first works of African cinema to depict postcolonial urban life from an African perspective.
-
E.
Simuka
Simuka was the founder and one of the earliest known kings of the Satavahana dynasty in ancient India.
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a700de48190aa9f61d850e01cbd |
completed | April 1, 2026, 1:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfebc90bf88190bbcdab07ca93f569 |
completed | April 3, 2026, 4:33 p.m. |
| NEDg | Description generation | batch_69cfecf7fce08190a9b80044a2ae9745 |
completed | April 3, 2026, 4:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cff0ea8c388190bd95233db9c69038 |
completed | April 3, 2026, 4:55 p.m. |
Created at: March 30, 2026, 7:10 p.m.