Triple
T1345491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Car Nicobar |
E28560
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Kima
Kima is a small settlement located on Car Nicobar Island in the Nicobar district of India’s Andaman and Nicobar Islands.
|
E153481
|
NE FINISHED |
How this triple was built (4 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: Kima | Statement: [Car Nicobar, hasSettlement, Kima]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kima Context triple: [Car Nicobar, hasSettlement, Kima]
-
A.
Sojin
Sojin is a given name, often used in East Asian cultures, that can refer to various individuals in entertainment, arts, and other fields.
-
B.
Hana
Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
-
C.
Hana
Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
-
D.
Kiko
Kiko is the young, albino giant ape who serves as the gentle offspring and companion of King Kong in the 1933 film "Son of Kong."
-
E.
Jin
Jin is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into Chinese society while preserving distinct communal identities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kima Triple: [Car Nicobar, hasSettlement, Kima]
Generated description
Kima is a small settlement located on Car Nicobar Island in the Nicobar district of India’s Andaman and Nicobar Islands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kima Target entity description: Kima is a small settlement located on Car Nicobar Island in the Nicobar district of India’s Andaman and Nicobar Islands.
-
A.
Sojin
Sojin is a given name, often used in East Asian cultures, that can refer to various individuals in entertainment, arts, and other fields.
-
B.
Hana
Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
-
C.
Hana
Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
-
D.
Kiko
Kiko is the young, albino giant ape who serves as the gentle offspring and companion of King Kong in the 1933 film "Son of Kong."
-
E.
Jin
Jin is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into Chinese society while preserving distinct communal identities.
- F. None of above. chosen
Provenance (5 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c23e84188190b0395c57dd45b62a |
completed | March 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc6351cbc81909e2ffc692ee92b54 |
completed | March 8, 2026, 12:43 a.m. |
| NEDg | Description generation | batch_69acc6af0db88190a02936072783553e |
completed | March 8, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc722d8608190acbef82f180b75d1 |
completed | March 8, 2026, 12:47 a.m. |
Created at: March 1, 2026, 7:56 p.m.