Triple
T11109362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daanbantayan |
E262714
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
Malingin
Malingin is a barangay (village-level administrative division) of the municipality of Daanbantayan in Cebu, Philippines.
|
E906334
|
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: Malingin | Statement: [Daanbantayan, hasBarangay, Malingin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malingin Context triple: [Daanbantayan, hasBarangay, Malingin]
-
A.
Malumfashi
Malumfashi is a town and local government area in northern Nigeria known for its role as an administrative and commercial center within Katsina State.
-
B.
Putatan
Putatan is a barangay and residential district within the city of Muntinlupa in Metro Manila, Philippines.
-
C.
Małdyty
Małdyty is a village and administrative center in northern Poland, situated in the Warmian-Masurian Voivodeship and known for its proximity to the region’s lakes and forests.
-
D.
Malakula
Malakula is one of the largest and most culturally diverse islands of Vanuatu, known for its many distinct languages and traditional customs.
-
E.
Matigari
Matigari is a political allegorical novel by Kenyan writer Ngũgĩ wa Thiong’o that critiques postcolonial corruption and injustice through the story of a returning freedom fighter.
- 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: Malingin Triple: [Daanbantayan, hasBarangay, Malingin]
Generated description
Malingin is a barangay (village-level administrative division) of the municipality of Daanbantayan in Cebu, Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Malingin Target entity description: Malingin is a barangay (village-level administrative division) of the municipality of Daanbantayan in Cebu, Philippines.
-
A.
Malumfashi
Malumfashi is a town and local government area in northern Nigeria known for its role as an administrative and commercial center within Katsina State.
-
B.
Putatan
Putatan is a barangay and residential district within the city of Muntinlupa in Metro Manila, Philippines.
-
C.
Małdyty
Małdyty is a village and administrative center in northern Poland, situated in the Warmian-Masurian Voivodeship and known for its proximity to the region’s lakes and forests.
-
D.
Malakula
Malakula is one of the largest and most culturally diverse islands of Vanuatu, known for its many distinct languages and traditional customs.
-
E.
Matigari
Matigari is a political allegorical novel by Kenyan writer Ngũgĩ wa Thiong’o that critiques postcolonial corruption and injustice through the story of a returning freedom fighter.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a6896c0819082685b5b4600d158 |
completed | April 9, 2026, 12:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d72f8f48190a7414119a6be9d5e |
completed | April 19, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69e4374700b881908ebb185ae020487b |
completed | April 19, 2026, 2 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4399385c08190852c3cbd730a1f11 |
completed | April 19, 2026, 2:10 a.m. |
Created at: April 8, 2026, 9:27 p.m.