Triple
T13479790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kandyan kings |
E318341
|
entity |
| Predicate | administrativeDivision |
P747
|
FINISHED |
| Object |
disavas
Disavas were regional administrative districts in the Kandyan Kingdom of Sri Lanka, each governed by an official responsible for local governance, revenue collection, and military duties.
|
E1042430
|
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: disavas | Statement: [Kandyan kings, administrativeDivision, disavas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: disavas Context triple: [Kandyan kings, administrativeDivision, disavas]
-
A.
Diss
Diss is a historic market town in eastern England known for its picturesque mere and traditional town center.
-
B.
Dis
Dis is the fortified infernal city in Dante Alighieri’s "Inferno," marking the deeper, more grievous circles of Hell.
-
C.
Dis
Dis is an alternate name for Pluto, the Roman god of the underworld and wealth.
-
D.
DIS
DIS is the station code assigned to MTR Disneyland Resort Station, the dedicated railway stop serving Hong Kong Disneyland.
-
E.
DIS
DIS is the stock ticker symbol for The Walt Disney Company, a major global entertainment and media conglomerate traded on the New York Stock Exchange.
- 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: disavas Triple: [Kandyan kings, administrativeDivision, disavas]
Generated description
Disavas were regional administrative districts in the Kandyan Kingdom of Sri Lanka, each governed by an official responsible for local governance, revenue collection, and military duties.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: disavas Target entity description: Disavas were regional administrative districts in the Kandyan Kingdom of Sri Lanka, each governed by an official responsible for local governance, revenue collection, and military duties.
-
A.
Diss
Diss is a historic market town in eastern England known for its picturesque mere and traditional town center.
-
B.
Dis
Dis is an alternate name for Pluto, the Roman god of the underworld and wealth.
-
C.
Dis
Dis is the fortified infernal city in Dante Alighieri’s "Inferno," marking the deeper, more grievous circles of Hell.
-
D.
DIS
DIS is the station code assigned to MTR Disneyland Resort Station, the dedicated railway stop serving Hong Kong Disneyland.
-
E.
DIS
DIS is the stock ticker symbol for The Walt Disney Company, a major global entertainment and media conglomerate traded on the New York Stock Exchange.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf36c6b08190ba99400600e0b662 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7463340fc8190b1128bd1d26f91ab |
completed | May 3, 2026, 12:57 p.m. |
| NEDg | Description generation | batch_69f747fee42c819097ccfaf01b1bf4da |
completed | May 3, 2026, 1:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f748bfc1a481908c3a86018533e45d |
completed | May 3, 2026, 1:08 p.m. |
Created at: April 9, 2026, 9:42 p.m.