Triple
T24022463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex and the City (newspaper column) |
E594860
|
entity |
| Predicate | originalNetworkOfAdaptation |
P154899
|
FINISHED |
| Object | HBO |
E18702
|
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: HBO | Statement: [Sex and the City (newspaper column), originalNetworkOfAdaptation, HBO]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalNetworkOfAdaptation Context triple: [Sex and the City (newspaper column), originalNetworkOfAdaptation, HBO]
-
A.
originalNetwork
Indicates that one entity is the original or source network from which another network or derived entity is based or obtained.
-
B.
originalNetworkDepicted
Indicates that one entity visually represents or portrays the original network associated with another entity.
-
C.
originalNetworkOrFormat
Indicates the network, platform, or format in which a work was first originally released or presented.
-
D.
adaptationOrigin
Indicates the source or basis from which an adaptation is derived or developed.
-
E.
originalNetworkName
Indicates the name of the network from which something (e.g., data, content, or a connection) originally came.
- F. None of above. chosen
Provenance (5 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_69e288be2c288190a3a46006945557f7 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d7667ff08190bfd14aa4eb776f21 |
completed | April 29, 2026, 10:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0f7ea5d23c8190b911c1c063668bdf |
completed | May 21, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 9:52 p.m.