Triple
T33701460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sybil Birling |
E863464
|
entity |
| Predicate | relationshipToInspector |
P206641
|
FINISHED |
| Object | hostile |
—
|
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: hostile | Statement: [Sybil Birling, relationshipToInspector, hostile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToInspector Context triple: [Sybil Birling, relationshipToInspector, hostile]
-
A.
relationshipToAuthorities
Indicates the nature or type of connection, role, or standing that an entity has in relation to governing or official authorities.
-
B.
relationshipToEleanorVance
Indicates the specific nature or type of relationship an entity has with Eleanor Vance.
-
C.
relationshipToDrWatson
Indicates the specific personal or professional relationship an entity has with Dr. Watson.
-
D.
relationshipToARP
Indicates a specified type of relationship or association that an entity has to an ARP (which may represent a particular person, program, plan, or reference point).
-
E.
relationshipToScout
Indicates the type or nature of a relationship that an entity has with a scout.
- F. None of above. chosen
Provenance (4 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:43 a.m.