Triple
T3973701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zoroaster |
E85590
|
entity |
| Predicate | associatedText |
P8272
|
FINISHED |
| Object | Avesta |
E85589
|
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: Avesta | Statement: [Zoroaster, associatedText, Avesta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avesta Context triple: [Zoroaster, associatedText, Avesta]
-
A.
Avesta
chosen
The Avesta is the primary collection of sacred scriptures of Zoroastrianism, containing hymns, liturgical texts, and religious teachings.
-
B.
Shahnameh
Shahnameh is an epic poem by Ferdowsi that recounts the mythological and historical past of Greater Iran and is considered one of the most important works of Persian literature.
-
C.
Vedas
The Vedas are a collection of ancient sacred texts composed in Sanskrit that form the foundational spiritual and philosophical scriptures of Hinduism.
-
D.
Shahnama-e-Islam
Shahnama-e-Islam is an epic Urdu poetic work that narrates Islamic history and heroes in a grand, literary style.
-
E.
Volume of the Sacred Law
The Volume of the Sacred Law is the holy book or books placed on the altar in Masonic lodges, representing divine truth according to the faiths of the members present.
- 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_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef99837cc8190b8b2464707f5e334 |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5628ab3ec8190aaaf7803f9f992af |
completed | March 14, 2026, 1:28 p.m. |
Created at: March 9, 2026, 3:32 p.m.