Triple
T22404296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teresa |
E553842
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Tessa |
E213395
|
NE FINISHED |
How this triple was built (2 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: Tessa | Statement: [Teresa, hasVariant, Tessa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessa Context triple: [Teresa, hasVariant, Tessa]
-
A.
Tessa
chosen
Tessa is a feminine given name commonly used in English-speaking countries, often as a diminutive of Theresa or Therese.
-
B.
Tessa Leah
Tessa Leah is a notable member of the Leah family, recognized for her significance within that family lineage.
-
C.
Tessa Lorraine
Tessa Lorraine is the central protagonist of the television drama series "American Soul," which chronicles the rise of Don Cornelius and the creation of the iconic music and dance show "Soul Train."
-
D.
Tamsin
Tamsin is a feminine given name of English origin, often associated with actresses and public figures such as Tamsin Egerton.
-
E.
Tessa Scott
Tessa Scott is a terminally ill teenage girl who creates and pursues a bold bucket list while confronting love, family, and mortality in the novel and film "Now Is Good."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b6762c8190991fc14c5ca8e609 |
completed | April 29, 2026, 1:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae9cfabe081908d6a001bcfe5372c |
completed | May 18, 2026, 10:28 a.m. |
Created at: April 16, 2026, 8:46 p.m.