Triple
T3725066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yod |
E81727
|
entity |
| Predicate | ISO15924 |
P11937
|
FINISHED |
| Object | Hebr |
E318982
|
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: Hebr | Statement: [Yod, ISO15924, Hebr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hebr Context triple: [Yod, ISO15924, Hebr]
-
A.
Hebr
chosen
Hebr is the ISO 15924 four-letter code that designates the Hebrew script used for writing the Hebrew language and several other Jewish languages.
-
B.
Halkomelem
Halkomelem is a Central Coast Salish Indigenous language traditionally spoken in southwestern British Columbia, Canada, particularly around the lower Fraser River and nearby coastal areas.
-
C.
Hohola
Hohola is a residential suburb and local area within Port Moresby, the capital city of Papua New Guinea.
-
D.
Haketia
Haketia is a Judeo-Spanish dialect historically spoken by Sephardic Jews in northern Morocco and parts of Gibraltar, characterized by strong influences from Moroccan Arabic and Hebrew.
-
E.
Ha language
Ha language is a Bantu language spoken primarily by the Ha people in western Tanzania, particularly around the shores of Lake Tanganyika.
- 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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcaf54af881908bd8d520595de061 |
completed | March 8, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4ce1e303881909efc1c6735d6c12e |
completed | March 14, 2026, 2:55 a.m. |
Created at: March 8, 2026, 3:34 p.m.