Triple
T9123407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LIP |
E218913
|
entity |
| Predicate | usedInTown |
P87209
|
FINISHED |
| Object |
Kalletal
Kalletal is a municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and location in the Teutoburg Forest region.
|
E780788
|
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: Kalletal | Statement: [LIP, usedInTown, Kalletal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kalletal Context triple: [LIP, usedInTown, Kalletal]
-
A.
Kallaṭa
Kallaṭa was an early Kashmiri Shaiva philosopher and disciple of Vasugupta, best known for his influential commentary on the Spanda Karikas that helped systematize the Spanda school of non-dual Shaivism.
-
B.
Kallady
Kallady is a coastal village in eastern Sri Lanka known for its beaches, fishing community, and proximity to the town of Batticaloa.
-
C.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
D.
Kaledupa
Kaledupa is an island in Indonesia’s Wakatobi archipelago, known for its traditional villages, mangrove forests, and rich surrounding coral reefs.
-
E.
Kalabahi
Kalabahi is the main town and administrative center on Alor Island in Indonesia’s East Nusa Tenggara province.
- 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: Kalletal Triple: [LIP, usedInTown, Kalletal]
Generated description
Kalletal is a municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and location in the Teutoburg Forest region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kalletal Target entity description: Kalletal is a municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and location in the Teutoburg Forest region.
-
A.
Kallaṭa
Kallaṭa was an early Kashmiri Shaiva philosopher and disciple of Vasugupta, best known for his influential commentary on the Spanda Karikas that helped systematize the Spanda school of non-dual Shaivism.
-
B.
Kallady
Kallady is a coastal village in eastern Sri Lanka known for its beaches, fishing community, and proximity to the town of Batticaloa.
-
C.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
D.
Kaledupa
Kaledupa is an island in Indonesia’s Wakatobi archipelago, known for its traditional villages, mangrove forests, and rich surrounding coral reefs.
-
E.
Kalabahi
Kalabahi is the main town and administrative center on Alor Island in Indonesia’s East Nusa Tenggara province.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d047c55a988190bf2dd63a0d0a2743 |
completed | April 3, 2026, 11:05 p.m. |
| NEDg | Description generation | batch_69d048dbcfe08190afb6ee816e22ddfc |
completed | April 3, 2026, 11:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d049b159d08190ad426bb7f9bcafb1 |
completed | April 3, 2026, 11:13 p.m. |
Created at: March 30, 2026, 7:17 p.m.