Triple
T7823123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Egon |
E181179
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object |
Nangatobong
Nangatobong is a settlement located in the vicinity of Mount Egon on the island of Flores in Indonesia.
|
E695170
|
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: Nangatobong | Statement: [Mount Egon, nearbySettlement, Nangatobong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nangatobong Context triple: [Mount Egon, nearbySettlement, Nangatobong]
-
A.
Binongko
Binongko is an island in Indonesia’s Wakatobi archipelago, known for its traditional blacksmithing culture and remote, rugged coastal landscapes.
-
B.
Tilantongo
Tilantongo was a prominent pre-Columbian Mixtec city-state in present-day Oaxaca, Mexico, known as a political and cultural hub of the Mixtec civilization.
-
C.
Tagabawa
Tagabawa is an Austronesian language spoken by the Bagobo-Tagabawa people of Mindanao in the southern Philippines.
-
D.
Tominanga
Tominanga is a dialect of the Kaili language spoken by communities in Central Sulawesi, Indonesia.
-
E.
Pantabangan
Pantabangan is a municipality in the Philippine province of Nueva Ecija known for the Pantabangan Dam and its role in irrigation and hydroelectric power generation.
- 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: Nangatobong Triple: [Mount Egon, nearbySettlement, Nangatobong]
Generated description
Nangatobong is a settlement located in the vicinity of Mount Egon on the island of Flores in Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nangatobong Target entity description: Nangatobong is a settlement located in the vicinity of Mount Egon on the island of Flores in Indonesia.
-
A.
Binongko
Binongko is an island in Indonesia’s Wakatobi archipelago, known for its traditional blacksmithing culture and remote, rugged coastal landscapes.
-
B.
Tilantongo
Tilantongo was a prominent pre-Columbian Mixtec city-state in present-day Oaxaca, Mexico, known as a political and cultural hub of the Mixtec civilization.
-
C.
Tagabawa
Tagabawa is an Austronesian language spoken by the Bagobo-Tagabawa people of Mindanao in the southern Philippines.
-
D.
Tominanga
Tominanga is a dialect of the Kaili language spoken by communities in Central Sulawesi, Indonesia.
-
E.
Pantabangan
Pantabangan is a municipality in the Philippine province of Nueva Ecija known for the Pantabangan Dam and its role in irrigation and hydroelectric power generation.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cafa095d7081908b3e492ce58b5d5f |
completed | March 30, 2026, 10:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14a526cc8190a8b1a3179f75ad6c |
completed | March 31, 2026, 12:26 a.m. |
| NEDg | Description generation | batch_69cb1734159881909590ed51e8920387 |
completed | March 31, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a6fc16c8190827593f58b9d742d |
completed | March 31, 2026, 12:50 a.m. |
Created at: March 30, 2026, 4:42 p.m.