Triple
T6969831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telugu literature |
E161572
|
entity |
| Predicate | hasNotableAuthor |
P4244
|
FINISHED |
| Object | Tikkana |
E34330
|
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: Tikkana | Statement: [Telugu literature, hasNotableAuthor, Tikkana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tikkana Context triple: [Telugu literature, hasNotableAuthor, Tikkana]
-
A.
Tikkana
chosen
Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
-
B.
Tiko
Tiko is a coastal town and port in southwestern Cameroon known for its agricultural activities and role as a transport hub.
-
C.
Tinée
Tinée is a river in southeastern France that flows through the Alpes-Maritimes department in the Provence-Alpes-Côte d'Azur region.
-
D.
Tuktukan
Tuktukan is a barangay (village-level administrative division) in the city of Taguig in Metro Manila, Philippines.
-
E.
Tchi-tchi
"Tchi-tchi" is a popular song performed by French singer and actor Tino Rossi, known for his romantic and melodic style.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db1649288190a52c7dab57b3c7dc |
completed | March 27, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7619ebab88190916e3d68068ed71d |
completed | March 28, 2026, 5:05 a.m. |
Created at: March 27, 2026, 2:30 p.m.