Triple
T17138599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pesisir Selatan Regency |
E415903
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lunang
Lunang is a district-level area within Indonesia’s Pesisir Selatan Regency in West Sumatra, known for its rural coastal and agricultural landscape.
|
E1252606
|
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: Lunang | Statement: [Pesisir Selatan Regency, contains, Lunang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lunang Context triple: [Pesisir Selatan Regency, contains, Lunang]
-
A.
Luhanka
Luhanka is a small rural municipality in central Finland known for its lakeside landscapes and tranquil countryside.
-
B.
Laoang
Laoang is a coastal municipality in the province of Northern Samar in the Philippines, known for its island landscapes and fishing communities.
-
C.
Lutayan
Lutayan is a municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and proximity to Lake Buluan.
-
D.
Menlale
Menlale is an alternative name for Mount Foraker, a prominent peak in the Alaska Range and one of the highest mountains in North America.
-
E.
Lukung
Lukung is a small village in the Ladakh region of India that serves as a gateway and popular stopover for visitors to the high-altitude Pangong Tso lake.
- 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: Lunang Triple: [Pesisir Selatan Regency, contains, Lunang]
Generated description
Lunang is a district-level area within Indonesia’s Pesisir Selatan Regency in West Sumatra, known for its rural coastal and agricultural landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lunang Target entity description: Lunang is a district-level area within Indonesia’s Pesisir Selatan Regency in West Sumatra, known for its rural coastal and agricultural landscape.
-
A.
Luhanka
Luhanka is a small rural municipality in central Finland known for its lakeside landscapes and tranquil countryside.
-
B.
Laoang
Laoang is a coastal municipality in the province of Northern Samar in the Philippines, known for its island landscapes and fishing communities.
-
C.
Lutayan
Lutayan is a municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and proximity to Lake Buluan.
-
D.
Menlale
Menlale is an alternative name for Mount Foraker, a prominent peak in the Alaska Range and one of the highest mountains in North America.
-
E.
Lukung
Lukung is a small village in the Ladakh region of India that serves as a gateway and popular stopover for visitors to the high-altitude Pangong Tso lake.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d1277881909325ffd2a7aa4873 |
completed | April 18, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a014152da008190bbbff4147cfd8c5b |
completed | May 11, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_6a014209b11081908ed088a9bb18b73b |
completed | May 11, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0142ac95188190847f29cb0f8d15ed |
completed | May 11, 2026, 2:45 a.m. |
Created at: April 10, 2026, 5:36 a.m.