Triple
T4335731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ta Shemau |
E97457
|
entity |
| Predicate | counterpart |
P6587
|
FINISHED |
| Object | Ta Mehu |
E27390
|
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: Ta Mehu | Statement: [Ta Shemau, counterpart, Ta Mehu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ta Mehu Context triple: [Ta Shemau, counterpart, Ta Mehu]
-
A.
Ta-Mehu
chosen
Ta-Mehu is the ancient Egyptian name for Lower Egypt, the northern region of the Nile Valley encompassing the Nile Delta.
-
B.
Mekhu
Mekhu was an ancient Egyptian official and noble whose rock-cut tomb is located among the Tombs of the Nobles at Aswan.
-
C.
Mera
Mera is a powerful Atlantean warrior and sorceress from DC Comics, best known as Aquaman’s ally and queen of Atlantis.
-
D.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
E.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
- 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_69b3454662a481908fbcd0bbfaa3a0a4 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35152bfc88190ab5d53ca38f98d8a |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d0a9967481908828ceeb76ce4cbf |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:14 p.m.