Triple
T7957879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tree Without Roots |
E184784
|
entity |
| Predicate | isTranslationOf |
P2303
|
FINISHED |
| Object | Lalsalu |
E184784
|
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: Lalsalu | Statement: [Tree Without Roots, isTranslationOf, Lalsalu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lalsalu Context triple: [Tree Without Roots, isTranslationOf, Lalsalu]
-
A.
Lalsalu
chosen
Lalsalu is a classic Bengali novel by Syed Waliullah that explores religious hypocrisy and rural life in East Bengal.
-
B.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
C.
Lasusua
Lasusua is a town in Indonesia that serves as the administrative center of North Kolaka Regency in Southeast Sulawesi.
-
D.
Liluah
Liluah is a suburban locality in the Howrah district of West Bengal, India, known for its residential areas and railway facilities near Kolkata.
-
E.
Novilara
Novilara is an archaeological site and locality in the Marche region of Italy, known for its ancient Picene culture remains and notable funerary stelae.
- 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_69ca8293a2388190aace944d7ed9c0c0 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b7ebb24819094bc011d51ef63fb |
completed | March 31, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe072ef4c8190a8e078c5280913db |
completed | March 31, 2026, 2:55 p.m. |
Created at: March 30, 2026, 5:11 p.m.