Triple
T152324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porbandar State |
E3458
|
entity |
| Predicate | dynasty |
P1547
|
FINISHED |
| Object | Jadeja Rajput |
E18734
|
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: Jadeja Rajput | Statement: [Porbandar State, dynasty, Jadeja Rajput]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jadeja Rajput Context triple: [Porbandar State, dynasty, Jadeja Rajput]
-
A.
Neal Mohan
Neal Mohan is an Indian-American technology executive and digital advertising expert who serves as the CEO of YouTube.
-
B.
Jadeja Rajputs
chosen
The Jadeja Rajputs are a prominent Rajput clan of western India historically known for their warrior aristocracy and rule over several princely states in the Kathiawar and Kutch regions of Gujarat.
-
C.
Amara Namani
Amara Namani is a young, resourceful Jaeger pilot and central protagonist in the science fiction film "Pacific Rim: Uprising."
-
D.
Madhavi Malalgoda Ariyabandu
Madhavi Malalgoda Ariyabandu is a Sri Lankan peace and human rights advocate recognized internationally for her contributions to social justice and conflict resolution.
-
E.
Tariq Anwar
Tariq Anwar is a British film editor known for his acclaimed work on numerous major films, including the Academy Award–winning drama "The King’s Speech."
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580f55a88190b37b54ee0ed5ac7c |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2ce36ad848190baf0359475fc0c3e |
completed | Feb. 28, 2026, 11:15 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.