Triple
T10029510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parahyangan |
E204815
|
entity |
| Predicate | hasMountain |
P10602
|
FINISHED |
| Object |
Guntur
Guntur is a volcanic mountain in West Java, Indonesia, known for its geothermal activity and scenic hiking routes.
|
E878508
|
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: Guntur | Statement: [Parahyangan, hasMountain, Guntur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guntur Context triple: [Parahyangan, hasMountain, Guntur]
-
A.
Guntur
Guntur is a major city in the Indian state of Andhra Pradesh, known historically as an important administrative and commercial center in southeastern India.
-
B.
Kakinada
Kakinada is a coastal city in the Indian state of Andhra Pradesh, known for its port, seafood industry, and role as a regional commercial hub.
-
C.
Gudivada
Gudivada is a town in the Indian state of Andhra Pradesh known as a local commercial and educational center in the Krishna River delta region.
-
D.
Machilipatnam
Machilipatnam is a coastal city in the Indian state of Andhra Pradesh, historically known as a significant port and trading center on the Bay of Bengal.
-
E.
Guntakal
Guntakal is a major railway junction town in Andhra Pradesh, India, serving as an important transit hub on several key rail routes in southern India.
- 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: Guntur Triple: [Parahyangan, hasMountain, Guntur]
Generated description
Guntur is a volcanic mountain in West Java, Indonesia, known for its geothermal activity and scenic hiking routes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Guntur Target entity description: Guntur is a volcanic mountain in West Java, Indonesia, known for its geothermal activity and scenic hiking routes.
-
A.
Guntur
Guntur is a major city in the Indian state of Andhra Pradesh, known historically as an important administrative and commercial center in southeastern India.
-
B.
Kakinada
Kakinada is a coastal city in the Indian state of Andhra Pradesh, known for its port, seafood industry, and role as a regional commercial hub.
-
C.
Gudivada
Gudivada is a town in the Indian state of Andhra Pradesh known as a local commercial and educational center in the Krishna River delta region.
-
D.
Machilipatnam
Machilipatnam is a coastal city in the Indian state of Andhra Pradesh, historically known as a significant port and trading center on the Bay of Bengal.
-
E.
Guntakal
Guntakal is a major railway junction town in Andhra Pradesh, India, serving as an important transit hub on several key rail routes in southern India.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcde69bd08190a5c79ec8487dfff6 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98811fd3881909369e0f00f2a8267 |
completed | April 10, 2026, 11:30 p.m. |
| NEDg | Description generation | batch_69d98bf7a070819097b41b5018ef21f9 |
completed | April 10, 2026, 11:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98c5d0d088190bbcf08b3b5b14b49 |
completed | April 10, 2026, 11:48 p.m. |
Created at: March 30, 2026, 8:54 p.m.