Triple
T3509649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria Tennant |
E74163
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Tennant
Tennant is a British surname borne by various notable figures in the arts, sciences, and public life.
|
E363230
|
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: Tennant | Statement: [Victoria Tennant, familyName, Tennant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tennant Context triple: [Victoria Tennant, familyName, Tennant]
-
A.
Whitrow
Whitrow is an English surname most notably associated with the late British actor Benjamin Whitrow.
-
B.
Moffat
Moffat is a small spa town in Dumfries and Galloway, Scotland, historically known for its wool trade and as a popular tourist destination in the Southern Uplands.
-
C.
Tilbury Douglas
Tilbury Douglas is a UK-based engineering and construction company known for delivering major infrastructure and building projects, including work on the London Eye.
-
D.
Gambon
Gambon is the surname of Sir Michael Gambon, the acclaimed Irish-English actor best known for portraying Albus Dumbledore in the Harry Potter film series.
-
E.
Pip Torrens
Pip Torrens is a British actor known for his character roles in film and television, including appearances in series such as "Patrick Melrose," "The Crown," and "Preacher."
- 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: Tennant Triple: [Victoria Tennant, familyName, Tennant]
Generated description
Tennant is a British surname borne by various notable figures in the arts, sciences, and public life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tennant Target entity description: Tennant is a British surname borne by various notable figures in the arts, sciences, and public life.
-
A.
Whitrow
Whitrow is an English surname most notably associated with the late British actor Benjamin Whitrow.
-
B.
Moffat
Moffat is a small spa town in Dumfries and Galloway, Scotland, historically known for its wool trade and as a popular tourist destination in the Southern Uplands.
-
C.
Tilbury Douglas
Tilbury Douglas is a UK-based engineering and construction company known for delivering major infrastructure and building projects, including work on the London Eye.
-
D.
Gambon
Gambon is the surname of Sir Michael Gambon, the acclaimed Irish-English actor best known for portraying Albus Dumbledore in the Harry Potter film series.
-
E.
Pip Torrens
Pip Torrens is a British actor known for his character roles in film and television, including appearances in series such as "Patrick Melrose," "The Crown," and "Preacher."
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc0e1f0c8190b054d9fba16ce4b3 |
completed | March 8, 2026, 6:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373e71ae8819096ea39955c92076a |
completed | March 13, 2026, 2:18 a.m. |
| NEDg | Description generation | batch_69b374e50a088190ad4dc101efd68d54 |
completed | March 13, 2026, 2:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b37544b04c819090e6f59babd8017e |
completed | March 13, 2026, 2:24 a.m. |
Created at: March 8, 2026, 3:18 p.m.