Triple
T22356255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ravi Shastri |
E552659
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Shastri |
—
|
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: Shastri | Statement: [Ravi Shastri, familyName, Shastri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shastri Context triple: [Ravi Shastri, familyName, Shastri]
-
A.
Shastri
chosen
Shastri is an honorific title in India traditionally bestowed upon scholars who have attained a high level of expertise in Sanskrit and Hindu scriptures.
-
B.
Anil Shastri
Anil Shastri is an Indian politician from the Indian National Congress and the son of former Prime Minister Lal Bahadur Shastri.
-
C.
Yashpal
Yashpal was an Indian revolutionary and later a noted Hindi writer known for his socialist views and politically charged novels.
-
D.
Kumar Pallana
Kumar Pallana was an Indian-American character actor and performer known for his quirky supporting roles in several Wes Anderson films and in Steven Spielberg’s "The Terminal."
-
E.
Jitendra Shastri
Jitendra Shastri was an Indian actor known for his character roles in Hindi films and television.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157cf94508190b0f2c63ddfecb813 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:44 p.m.