Triple
T3233660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How I Got Over |
E67799
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Web 20/20 |
E3289
|
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: Web 20/20 | Statement: [How I Got Over, hasPart, Web 20/20]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Web 20/20 Context triple: [How I Got Over, hasPart, Web 20/20]
-
A.
Web 2.0
chosen
Web 2.0 refers to the second generation of the World Wide Web characterized by user-generated content, social media, interactivity, and collaboration on platforms such as blogs, wikis, and social networks.
-
B.
The Interne
The Interne is a novel by Harlem Renaissance writer Wallace Thurman that explores the experiences and challenges of a young Black medical intern in early 20th-century America.
-
C.
The Net
The Net is a 1995 techno-thriller film starring Sandra Bullock as a computer analyst whose identity is erased by cybercriminals, directed by Irwin Winkler.
-
D.
Port 2000
Port 2000 is a major deep-water container terminal complex at the Port of Le Havre in France, designed to handle large modern cargo ships and increase the port’s capacity.
-
E.
Cyber-Shades
Cyber-Shades are a variant of the Cybermen in Doctor Who, characterized by their bestial, hound-like form used for tracking and capturing victims.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaedcd9588190b3623f0109d653a4 |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2773b494c8190a2c0c5042e8eaa55 |
completed | March 12, 2026, 8:20 a.m. |
Created at: March 8, 2026, 3:08 p.m.