Triple
T3507863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian campaign |
E74120
|
entity |
| Predicate | hasParticipant |
P149
|
FINISHED |
| Object | King Porus |
E151794
|
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: King Porus | Statement: [Indian campaign, hasParticipant, King Porus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: King Porus Context triple: [Indian campaign, hasParticipant, King Porus]
-
A.
King Porus
chosen
King Porus was an ancient Indian ruler of the Punjab region, renowned for his valiant resistance against Alexander the Great during the Battle of the Hydaspes.
-
B.
Raja Dahir
Raja Dahir was the last Hindu ruler of Sindh, known for his defeat and death in 712 CE during the Arab conquest of the region led by Muhammad bin Qasim.
-
C.
Shershah
Shershah is a locality in Karachi, Pakistan, known for its industrial zones, warehouses, and commercial activity.
-
D.
Rajasuya
Rajasuya is an ancient Vedic royal consecration ritual performed to legitimize and exalt a king’s sovereignty and supreme status.
-
E.
Meghnad
Meghnad is a given name most notably associated with Indian astrophysicist Meghnad Saha, renowned for his pioneering work on thermal ionization and stellar spectra.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc0b635c81909bc95ba2562d8f94 |
completed | March 8, 2026, 6:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373e3cd808190807d4acae2942a9d |
completed | March 13, 2026, 2:18 a.m. |
Created at: March 8, 2026, 3:18 p.m.