Triple
T14179561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salammbô |
E351416
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Matho
Matho is a passionate and tragic Libyan mercenary leader in Gustave Flaubert’s historical novel "Salammbô."
|
E1084665
|
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: Matho | Statement: [Salammbô, mainCharacter, Matho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matho Context triple: [Salammbô, mainCharacter, Matho]
-
A.
Le Mat
Le Mat is a surname most notably associated with American actor Paul Le Mat, known for his role in the film "American Graffiti."
-
B.
Mazo
Mazo is a locality situated on the border of the municipality of El Paso in the Canary Island of La Palma, Spain.
-
C.
Múzquiz
Múzquiz is a metro station in the Mexico City Metro system, serving passengers on Line B in the northeastern part of the metropolitan area.
-
D.
Tentyris
Tentyris is the ancient Greek name for the Egyptian city of Dendera, renowned for its well-preserved temple complex dedicated primarily to the goddess Hathor.
-
E.
Trichinopoly
Trichinopoly, now commonly known as Tiruchirappalli, is a historic city in Tamil Nadu, India, renowned for its ancient temples and strategic location on the banks of the Kaveri River.
- 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: Matho Triple: [Salammbô, mainCharacter, Matho]
Generated description
Matho is a passionate and tragic Libyan mercenary leader in Gustave Flaubert’s historical novel "Salammbô."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matho Target entity description: Matho is a passionate and tragic Libyan mercenary leader in Gustave Flaubert’s historical novel "Salammbô."
-
A.
Le Mat
Le Mat is a surname most notably associated with American actor Paul Le Mat, known for his role in the film "American Graffiti."
-
B.
Mazo
Mazo is a locality situated on the border of the municipality of El Paso in the Canary Island of La Palma, Spain.
-
C.
Múzquiz
Múzquiz is a metro station in the Mexico City Metro system, serving passengers on Line B in the northeastern part of the metropolitan area.
-
D.
Tentyris
Tentyris is the ancient Greek name for the Egyptian city of Dendera, renowned for its well-preserved temple complex dedicated primarily to the goddess Hathor.
-
E.
Trichinopoly
Trichinopoly, now commonly known as Tiruchirappalli, is a historic city in Tamil Nadu, India, renowned for its ancient temples and strategic location on the banks of the Kaveri River.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61c90abc8190a9b9dc1f50db59fa |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf80f03a48190a5374fb6374255a8 |
completed | May 7, 2026, 8:37 p.m. |
| NEDg | Description generation | batch_69fd09b00dc48190bec9853e3dc78f26 |
completed | May 7, 2026, 9:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd0a4c377c81909af76e8bd47e2f2a |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 10, 2026, 1:02 a.m.