Triple
T1302832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arba’ah Turim |
E27805
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Tur |
E54375
|
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: Tur | Statement: [Arba’ah Turim, alsoKnownAs, Tur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tur Context triple: [Arba’ah Turim, alsoKnownAs, Tur]
-
A.
Tur
chosen
Tur is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organized halakhic rulings and served as a primary basis for later works like the Shulchan Aruch.
-
B.
TOR
TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
-
C.
Tan
Tan is a surname and given name commonly found in various East and Southeast Asian cultures, often representing a romanization of different Chinese family names.
-
D.
Tek
Tek is a brand associated with Tektronix, known for electronic test and measurement equipment such as oscilloscopes and signal analyzers.
-
E.
Tus
Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c115ba64819081c55fa6807e19ef |
completed | March 1, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acb3046a888190956f6bedb6ec589f |
completed | March 7, 2026, 11:21 p.m. |
Created at: March 1, 2026, 7:51 p.m.