Triple
T10630684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamara |
E250443
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Tam |
E399455
|
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: Tam | Statement: [Tamara, hasDiminutive, Tam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tam Context triple: [Tamara, hasDiminutive, Tam]
-
A.
Tam
chosen
Tam is a key crew member and engineer aboard the space station in the science fiction horror film "The Cloverfield Paradox."
-
B.
Tam
Tam is the commonly used abbreviation for Tamalpais High School, a public high school in Mill Valley, California.
-
C.
Tan
Tan is a surname and given name commonly found in various East and Southeast Asian cultures, often representing a romanization of different Chinese family names.
-
D.
Tom
Tom is a common masculine given name, often used in English-speaking countries as a short form of Thomas.
-
E.
Tar
Tar is a diminutive form of the given name Tara, often used as a casual or affectionate nickname.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df93a2b88190a0f3a52b8e88f54f |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96bb4bbf08190994ea9123c0b2dab |
completed | April 10, 2026, 9:29 p.m. |
Created at: April 8, 2026, 9:01 p.m.