Triple
T13951738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian La Frenais |
E335542
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
La Frenais
La Frenais is a surname most notably associated with British television writer Ian La Frenais, known for co-creating several classic UK comedy series.
|
E1071203
|
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: La Frenais | Statement: [Ian La Frenais, familyName, La Frenais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Frenais Context triple: [Ian La Frenais, familyName, La Frenais]
-
A.
Leschenault de La Tour
Leschenault de La Tour was a French botanist and explorer after whom Western Australia’s Leschenault Inlet is named.
-
B.
Le Joly
Le Joly was a French ship associated with the 17th-century explorer René-Robert Cavelier, Sieur de La Salle, used during his expeditions in North America.
-
C.
de Montferrand
de Montferrand is the French noble family name borne by architect Auguste de Montferrand, renowned for designing Saint Isaac's Cathedral in Saint Petersburg.
-
D.
Le Fayet
Le Fayet is a village in the French Alps that serves as a gateway and lower terminus for the historic Tramway du Mont-Blanc mountain railway.
-
E.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
- 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: La Frenais Triple: [Ian La Frenais, familyName, La Frenais]
Generated description
La Frenais is a surname most notably associated with British television writer Ian La Frenais, known for co-creating several classic UK comedy series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Frenais Target entity description: La Frenais is a surname most notably associated with British television writer Ian La Frenais, known for co-creating several classic UK comedy series.
-
A.
Leschenault de La Tour
Leschenault de La Tour was a French botanist and explorer after whom Western Australia’s Leschenault Inlet is named.
-
B.
Le Joly
Le Joly was a French ship associated with the 17th-century explorer René-Robert Cavelier, Sieur de La Salle, used during his expeditions in North America.
-
C.
de Montferrand
de Montferrand is the French noble family name borne by architect Auguste de Montferrand, renowned for designing Saint Isaac's Cathedral in Saint Petersburg.
-
D.
Le Fayet
Le Fayet is a village in the French Alps that serves as a gateway and lower terminus for the historic Tramway du Mont-Blanc mountain railway.
-
E.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e131c608190b4ffdbada24a3208 |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1cea88081908c37836447410b97 |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba53a14c48190a5f954a73a9ca42c |
completed | May 6, 2026, 8:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba5c481fc8190bda5bb4afaf85288 |
completed | May 6, 2026, 8:34 p.m. |
Created at: April 9, 2026, 10:17 p.m.