Triple
T35385764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Shaibel |
E1022787
|
entity |
| Predicate | relationshipToBethHarmon |
P192822
|
FINISHED |
| Object | first chess teacher |
—
|
LITERAL 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: first chess teacher | Statement: [Mr. Shaibel, relationshipToBethHarmon, first chess teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToBethHarmon Context triple: [Mr. Shaibel, relationshipToBethHarmon, first chess teacher]
-
A.
relationshipToBeth
chosen
Indicates the specific type of relationship or connection that an entity has to Beth.
-
B.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
C.
relationshipToSamanthaGrimm
Indicates the specific type of relationship or connection an entity has to Samantha Grimm.
-
D.
relationshipToKittyBennet
Indicates the specific type of personal or familial connection an entity has to Kitty Bennet.
-
E.
relationshipToEvanHansen
Indicates the type or nature of a person's relationship or connection to Evan Hansen.
- F. None of above.
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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:03 p.m.