Triple
T20025548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Leyte |
E494972
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Matag-ob
Matag-ob is a municipality in the province of Leyte in the Philippines, known for its rural communities and agricultural landscape.
|
E1407525
|
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: Matag-ob | Statement: [Province of Leyte, hasMunicipality, Matag-ob]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matag-ob Context triple: [Province of Leyte, hasMunicipality, Matag-ob]
-
A.
Matagot
Matagot is a French board game publisher known for producing innovative and thematic tabletop games.
-
B.
Manghit
Manghit was a Central Asian tribal group that rose to prominence as the ruling clan of the Manghit (Bukhara) dynasty.
-
C.
Morungaba
Morungaba is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and integration into the economically significant Campinas metropolitan area.
-
D.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
-
E.
Mang’ati
Mang’ati is an alternative name for the Datooga, a Nilotic-speaking pastoralist ethnic group primarily living in northern Tanzania.
- 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: Matag-ob Triple: [Province of Leyte, hasMunicipality, Matag-ob]
Generated description
Matag-ob is a municipality in the province of Leyte in the Philippines, known for its rural communities and agricultural landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matag-ob Target entity description: Matag-ob is a municipality in the province of Leyte in the Philippines, known for its rural communities and agricultural landscape.
-
A.
Matagot
Matagot is a French board game publisher known for producing innovative and thematic tabletop games.
-
B.
Manghit
Manghit was a Central Asian tribal group that rose to prominence as the ruling clan of the Manghit (Bukhara) dynasty.
-
C.
Morungaba
Morungaba is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and integration into the economically significant Campinas metropolitan area.
-
D.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
-
E.
Mang’ati
Mang’ati is an alternative name for the Datooga, a Nilotic-speaking pastoralist ethnic group primarily living in northern Tanzania.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6628d5b8c8190a35f95ac4a016550 |
completed | April 20, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a080e2f549c8190b04f8470fbb63a0c |
completed | May 16, 2026, 6:26 a.m. |
| NEDg | Description generation | batch_6a080f393dc0819093fec526d1b51dac |
completed | May 16, 2026, 6:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0810234a788190b329c55e553b365e |
completed | May 16, 2026, 6:35 a.m. |
Created at: April 11, 2026, 3:35 p.m.