Triple
T22092741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tana French |
E545949
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Tana
Tana is the given name of Irish crime novelist Tana French, known for her Dublin Murder Squad series.
|
E1519612
|
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: Tana | Statement: [Tana French, givenName, Tana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tana Context triple: [Tana French, givenName, Tana]
-
A.
Tana
Tana was a medieval Genoese trading colony and port on the Sea of Azov that served as a key hub for commerce between Europe and Asia.
-
B.
Tana
Tana is the commonly used nickname for Antananarivo, the capital and largest city of Madagascar.
-
C.
Tana
Tana is a sparsely populated municipality in Troms og Finnmark county in northern Norway, known for the Tana River, rich salmon fishing, and strong Sámi cultural heritage.
-
D.
Tana Rivera
Tana Rivera is a Spanish aristocrat and media personality, best known as the daughter of socialite and noblewoman Eugenia Martínez de Irujo and bullfighter Francisco Rivera Ordóñez.
-
E.
Kolyma River
The Kolyma River is a major waterway in northeastern Siberia, Russia, known for its harsh Arctic environment and historical association with Soviet-era labor camps.
- 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: Tana Triple: [Tana French, givenName, Tana]
Generated description
Tana is the given name of Irish crime novelist Tana French, known for her Dublin Murder Squad series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tana Target entity description: Tana is the given name of Irish crime novelist Tana French, known for her Dublin Murder Squad series.
-
A.
Tana
Tana was a medieval Genoese trading colony and port on the Sea of Azov that served as a key hub for commerce between Europe and Asia.
-
B.
Tana
Tana is the commonly used nickname for Antananarivo, the capital and largest city of Madagascar.
-
C.
Tana
Tana is a sparsely populated municipality in Troms og Finnmark county in northern Norway, known for the Tana River, rich salmon fishing, and strong Sámi cultural heritage.
-
D.
Tana Rivera
Tana Rivera is a Spanish aristocrat and media personality, best known as the daughter of socialite and noblewoman Eugenia Martínez de Irujo and bullfighter Francisco Rivera Ordóñez.
-
E.
Kolyma River
The Kolyma River is a major waterway in northeastern Siberia, Russia, known for its harsh Arctic environment and historical association with Soviet-era labor camps.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e6b1d881909bf0f4a52199354c |
completed | April 28, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a8f117f7c8190b34b3bd32eb0e97d |
completed | May 18, 2026, 4:01 a.m. |
| NEDg | Description generation | batch_6a0a90ca49c48190b01c88ae7e841cb4 |
completed | May 18, 2026, 4:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a915bd5748190afc5a5a6e9398564 |
completed | May 18, 2026, 4:11 a.m. |
Created at: April 16, 2026, 8:29 p.m.