Triple
T8730064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nehase |
E207231
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Hamle |
E753708
|
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: Hamle | Statement: [Nehase, follows, Hamle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamle Context triple: [Nehase, follows, Hamle]
-
A.
Hamle
chosen
Hamle is the eleventh month of the Ethiopian calendar, roughly corresponding to July in the Gregorian calendar.
-
B.
Hemulen
Hemulen is a character from Tove Jansson’s Moomin series, typically portrayed as a tall, earnest, and somewhat pedantic creature obsessed with hobbies like stamp collecting and botany.
-
C.
Hamey
Hamey is a diminutive or affectionate nickname derived from the given name Hamish.
-
D.
Heze
Heze is a prefecture-level city in southwestern Shandong Province, China, known as a major agricultural center and a famous hub for peony cultivation.
-
E.
Huelma
Huelma is a municipality in the province of Jaén, Andalusia, Spain, known for its rural setting and cultural landmarks.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d26d280819085e15d4917c2b9a5 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf42b0f5808190863a1ca3c4e9c8d1 |
completed | April 3, 2026, 4:31 a.m. |
Created at: March 30, 2026, 6:37 p.m.