Triple
T12145968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merenre Nemtyemsaf I |
E289322
|
entity |
| Predicate | nomen |
P744
|
FINISHED |
| Object |
Nemtyemsaf
Nemtyemsaf was an ancient Egyptian royal name borne by pharaohs of the Sixth Dynasty, notably Merenre Nemtyemsaf I.
|
E965475
|
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: Nemtyemsaf | Statement: [Merenre Nemtyemsaf I, nomen, Nemtyemsaf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nemtyemsaf Context triple: [Merenre Nemtyemsaf I, nomen, Nemtyemsaf]
-
A.
Neltume
Neltume is a small town in southern Chile known for its proximity to lakes, forests, and ecotourism activities in the Andes.
-
B.
Némi
Némi is an Oceanic language spoken by a small indigenous community in New Caledonia.
-
C.
Nadsiannia
Nadsiannia is a historical and ethnographic region of Eastern Europe associated with Ukrainian highlander culture and situated near the Lemko region.
-
D.
Nesuhi
Nesuhi was a prominent Turkish-American record producer and music executive best known for his influential work in jazz, particularly at Atlantic Records.
-
E.
Kelmis
Kelmis is a municipality in eastern Belgium located in the country's German-speaking region, known for its historical zinc mining industry and borderland character near Germany and the Netherlands.
- 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: Nemtyemsaf Triple: [Merenre Nemtyemsaf I, nomen, Nemtyemsaf]
Generated description
Nemtyemsaf was an ancient Egyptian royal name borne by pharaohs of the Sixth Dynasty, notably Merenre Nemtyemsaf I.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nemtyemsaf Target entity description: Nemtyemsaf was an ancient Egyptian royal name borne by pharaohs of the Sixth Dynasty, notably Merenre Nemtyemsaf I.
-
A.
Neltume
Neltume is a small town in southern Chile known for its proximity to lakes, forests, and ecotourism activities in the Andes.
-
B.
Némi
Némi is an Oceanic language spoken by a small indigenous community in New Caledonia.
-
C.
Nadsiannia
Nadsiannia is a historical and ethnographic region of Eastern Europe associated with Ukrainian highlander culture and situated near the Lemko region.
-
D.
Nesuhi
Nesuhi was a prominent Turkish-American record producer and music executive best known for his influential work in jazz, particularly at Atlantic Records.
-
E.
Kelmis
Kelmis is a municipality in eastern Belgium located in the country's German-speaking region, known for its historical zinc mining industry and borderland character near Germany and the Netherlands.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915ac2ebc81909155f9b2fb4a2252 |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f696ec648190aa43655ac8a2b312 |
completed | May 2, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69f600b7385881909ddb86a1d39ff5d4 |
completed | May 2, 2026, 1:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f601ebaa448190ba59485d9d7d68d1 |
completed | May 2, 2026, 1:53 p.m. |
Created at: April 8, 2026, 9:49 p.m.