Triple
T21844160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamshed |
E539331
|
entity |
| Predicate | hasAlternativeTransliteration |
P5923
|
FINISHED |
| Object | Jamsheed |
—
|
NE NERFINISHED |
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: Jamsheed | Statement: [Jamshed, hasAlternativeTransliteration, Jamsheed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jamsheed Context triple: [Jamshed, hasAlternativeTransliteration, Jamsheed]
-
A.
Jamshid
chosen
Jamshid is a legendary king in Persian mythology, renowned for his long, prosperous reign and his central role in ancient Iranian cultural and epic traditions.
-
B.
Shaukeen
Shaukeen is a 1982 Hindi comedy film about three elderly men seeking romantic adventure, directed by Basu Chatterjee and known for its lighthearted, character-driven humor.
-
C.
Mirza
Mirza is a historical noble title of Persian and Central Asian origin, commonly borne by princes and high-ranking members of royal and aristocratic families.
-
D.
Farhat
Farhat is a surname of Arabic origin borne by various individuals, including Tunisian figures such as Chadlia Saïda Farhat.
-
E.
Akthar
Akthar is an individual or entity known primarily through an association with Rudge, likely within a shared professional, academic, or organizational context.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0bd5248f08190ba208512eafbe7ad |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 16, 2026, 6:55 p.m.