Triple
T16828005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cañas y barro |
E409070
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Tonet
Tonet is a central character in Vicente Blasco Ibáñez’s novel "Cañas y barro," representing the struggles and passions of rural life in Spain’s Albufera region.
|
E1235393
|
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: Tonet | Statement: [Cañas y barro, mainCharacter, Tonet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tonet Context triple: [Cañas y barro, mainCharacter, Tonet]
-
A.
TONA
TONA is Japan’s nearly risk-free overnight reference interest rate used as a key benchmark in financial markets, particularly as a replacement for LIBOR in yen-denominated contracts.
-
B.
The Ton
The Ton is the traditional nickname of Scottish football club Greenock Morton F.C., reflecting its long-standing identity and fan culture.
-
C.
Tolo
Tolo is an alternative name for the Talise language, an Austronesian language spoken in the Solomon Islands.
-
D.
Tolo
Tolo is a coastal village and popular tourist resort in the Argolis region of the Peloponnese in Greece, known for its beaches and proximity to historic sites like Nafplio.
-
E.
Taneti
Taneti is the given name of Taneti Maamau, the President of Kiribati.
- 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: Tonet Triple: [Cañas y barro, mainCharacter, Tonet]
Generated description
Tonet is a central character in Vicente Blasco Ibáñez’s novel "Cañas y barro," representing the struggles and passions of rural life in Spain’s Albufera region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tonet Target entity description: Tonet is a central character in Vicente Blasco Ibáñez’s novel "Cañas y barro," representing the struggles and passions of rural life in Spain’s Albufera region.
-
A.
TONA
TONA is Japan’s nearly risk-free overnight reference interest rate used as a key benchmark in financial markets, particularly as a replacement for LIBOR in yen-denominated contracts.
-
B.
The Ton
The Ton is the traditional nickname of Scottish football club Greenock Morton F.C., reflecting its long-standing identity and fan culture.
-
C.
Tolo
Tolo is a coastal village and popular tourist resort in the Argolis region of the Peloponnese in Greece, known for its beaches and proximity to historic sites like Nafplio.
-
D.
Tolo
Tolo is an alternative name for the Talise language, an Austronesian language spoken in the Solomon Islands.
-
E.
Taneti
Taneti is the given name of Taneti Maamau, the President of Kiribati.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b3151350819097b1c375e6df8986 |
completed | April 18, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b2a0ac148190a7a7edebcb67c040 |
completed | May 10, 2026, 4:30 p.m. |
| NEDg | Description generation | batch_6a00b35ea8f88190ae33e8a2f906d133 |
completed | May 10, 2026, 4:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00b3d14b3c819081f435777f47eca3 |
completed | May 10, 2026, 4:35 p.m. |
Created at: April 10, 2026, 5:23 a.m.