Triple
T11793919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GMA Films |
E280456
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Muro Ami |
E733621
|
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: Muro Ami | Statement: [GMA Films, notableWork, Muro Ami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muro Ami Context triple: [GMA Films, notableWork, Muro Ami]
-
A.
Muro Ami
chosen
Muro Ami is a Filipino drama film that powerfully depicts the harsh realities of child labor in the destructive muro-ami fishing industry.
-
B.
Miho no Matsubara
Miho no Matsubara is a scenic coastal pine grove and beach in Shizuoka, Japan, famed for its views of Mount Fuji and its appearance in traditional art and folklore.
-
C.
Munefusa
Munefusa is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and travel writer.
-
D.
Komuro
Komuro is the married surname of Japan’s former Princess Mako, adopted after her marriage to commoner Kei Komuro.
-
E.
Akaiami
Akaiami is a small, picturesque islet in the Aitutaki Lagoon of the Cook Islands, known for its white-sand beaches and clear turquoise waters.
- 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_69d6ab258b808190b1735835c841e3a4 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a5a082d08190a42541396a06ed98 |
completed | April 10, 2026, 7:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f09115c66c8190b0a3e775bdf575c1 |
completed | April 28, 2026, 10:51 a.m. |
Created at: April 8, 2026, 9:42 p.m.