Triple
T10708818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herakleopolis Magna |
E252478
|
entity |
| Predicate | ancientName |
P2834
|
FINISHED |
| Object | Hnes |
E351948
|
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: Hnes | Statement: [Herakleopolis Magna, ancientName, Hnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hnes Context triple: [Herakleopolis Magna, ancientName, Hnes]
-
A.
Hnes
chosen
Hnes is an alternative name for Ihnasya al-Madinah, a historic town in Egypt known for its ancient archaeological significance.
-
B.
Nesite
Nesite is the term commonly used by modern scholars for the Hittite language, an ancient Indo-European language once spoken in Anatolia.
-
C.
Hodierna
Hodierna is an Italian surname most notably associated with the 17th-century astronomer Giovanni Battista Hodierna.
-
D.
Sarrainodu
Sarrainodu is a 2016 Indian Telugu-language action film known for its high-octane fight sequences, mass appeal, and Allu Arjun’s charismatic performance.
-
E.
Iferhounène
Iferhounène is a town and commune located in the mountainous Kabylie region of northern Algeria.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fe5063bc8190ba12fd68a59c9a03 |
completed | April 9, 2026, 1:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9990760b48190a05753974cdf556c |
completed | April 11, 2026, 12:42 a.m. |
Created at: April 8, 2026, 9:13 p.m.