Triple
T11824224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim |
E281218
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Teshoo Lama |
E658008
|
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: Teshoo Lama | Statement: [Kim, hasCharacter, Teshoo Lama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teshoo Lama Context triple: [Kim, hasCharacter, Teshoo Lama]
-
A.
Teshoo Lama
chosen
Teshoo Lama is a wise and compassionate Tibetan Buddhist monk who serves as a spiritual mentor and father figure to the orphaned protagonist in Rudyard Kipling’s novel "Kim."
-
B.
Lhakpa Tsamchoe
Lhakpa Tsamchoe is a Tibetan actress best known internationally for her role in the film "Seven Years in Tibet."
-
C.
Nyima Gyaltsen
Nyima Gyaltsen is a mountaineer known for leading the first successful ascent of Myanmar’s highest peak, Hkakabo Razi.
-
D.
Gyazumpa Cho
Gyazumpa Cho is one of the high-altitude glacial lakes in Nepal’s Gokyo Lakes system in the Everest region of the Himalayas.
-
E.
Phuntsog Namgyal
Phuntsog Namgyal was the first Chogyal (king) of Sikkim, who established the kingdom in the 17th century and laid the foundations of its monarchy.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5eb299481909de3c0e85628fbe4 |
completed | April 10, 2026, 7:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f131f4e2ec8190a78c101e17eaa5c0 |
completed | April 28, 2026, 10:17 p.m. |
Created at: April 8, 2026, 9:43 p.m.