Triple
T32895135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny Fleck |
E841448
|
entity |
| Predicate | relationshipToThomasWayne |
P205189
|
FINISHED |
| Object | former employee |
—
|
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: former employee | Statement: [Penny Fleck, relationshipToThomasWayne, former employee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToThomasWayne Context triple: [Penny Fleck, relationshipToThomasWayne, former employee]
-
A.
relationshipToClarkKent
Indicates the specific personal, social, or familial connection that one entity has to Clark Kent.
-
B.
relationshipToJonathanKent
Indicates the specific familial or personal relationship that an entity has to Jonathan Kent.
-
C.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
D.
relationshipWithTitans
Indicates a relationship or association that an entity has with one or more Titans, such as alliances, conflicts, or other significant interactions.
-
E.
roleInBatmanAndRobin
Indicates that an entity has a specific role or involvement in the context of "Batman and Robin" (such as the story, franchise, or related work).
- 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037cab06288190b093935f235ddff2 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:18 a.m.