Triple
T11166667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amala |
E264175
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Cambo
Cambo is a film producer associated with projects featuring actress Amala in Indian cinema.
|
E909680
|
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: Cambo | Statement: [Amala, producer, Cambo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cambo Context triple: [Amala, producer, Cambo]
-
A.
Kambos
Kambos is a coastal village on the Greek island of Patmos, known for its sandy beach and role as a popular summer resort area.
-
B.
Kambo
Kambo is a small village and residential area in Moss municipality in southeastern Norway.
-
C.
Camoapa
Camoapa is a municipality in central Nicaragua known for its cattle ranching, dairy production, and traditional rural culture.
-
D.
Cambodunum
Cambodunum was a major Roman settlement and administrative center in the province of Raetia, located near present-day Kempten in southern Germany.
-
E.
Kambojas
The Kambojas were an ancient Indo-Iranian people mentioned in Indian and Persian sources, known for their warrior traditions and presence in regions around present-day Afghanistan and northwestern South Asia.
- 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: Cambo Triple: [Amala, producer, Cambo]
Generated description
Cambo is a film producer associated with projects featuring actress Amala in Indian cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cambo Target entity description: Cambo is a film producer associated with projects featuring actress Amala in Indian cinema.
-
A.
Kambos
Kambos is a coastal village on the Greek island of Patmos, known for its sandy beach and role as a popular summer resort area.
-
B.
Kambo
Kambo is a small village and residential area in Moss municipality in southeastern Norway.
-
C.
Camoapa
Camoapa is a municipality in central Nicaragua known for its cattle ranching, dairy production, and traditional rural culture.
-
D.
Cambodunum
Cambodunum was a major Roman settlement and administrative center in the province of Raetia, located near present-day Kempten in southern Germany.
-
E.
Kambojas
The Kambojas were an ancient Indo-Iranian people mentioned in Indian and Persian sources, known for their warrior traditions and presence in regions around present-day Afghanistan and northwestern South Asia.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e88843cc81909e503f0921c6d297 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e483747ba88190aa6ef9df2545b18b |
completed | April 19, 2026, 7:25 a.m. |
| NEDg | Description generation | batch_69e485f46f0c81908dbe5b47322ab7b7 |
completed | April 19, 2026, 7:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4878dd95c81908ceaf91ee46f49c1 |
completed | April 19, 2026, 7:43 a.m. |
Created at: April 8, 2026, 9:29 p.m.